Using digital fingerprints to associate data with a work

Information

  • Patent Grant
  • 10698952
  • Patent Number
    10,698,952
  • Date Filed
    Monday, March 20, 2017
    7 years ago
  • Date Issued
    Tuesday, June 30, 2020
    4 years ago
  • CPC
  • Field of Search
    • US
    • 707 607000
    • 707 609000
    • 707 687000
    • 707 705000
    • 707 790000
    • 707 813000
    • 707 821000
    • CPC
    • G06F16/435
  • International Classifications
    • G06F16/30
    • G06F16/783
    • G06F16/43
    • G06F16/435
    • G06F16/683
    • G06F16/738
    • H04L9/32
    • Disclaimer
      This patent is subject to a terminal disclaimer.
      Term Extension
      382
Abstract
A computing device, during sampling or playback of a work, receives a command to associate data with the work at a particular point in the work. The computing device generates a digital fingerprint of a segment of the work, wherein the segment corresponds to the particular point in the work. The computing device then associates the data with the digital fingerprint.
Description
BACKGROUND OF THE INVENTION

Individuals often want to create annotations attached to points or segments in a work (for example, a video, a music recording, or the like) that can then be shared and used by others, or that they can access themselves when the work is replayed at a later time or different location. Standard methods of associating data with a work at a particular point in the work rely on using time offsets into the work such that there is an inherent risk in presenting the associated data too early or too late, thus diminishing a user experience.





BRIEF DESCRIPTION OF THE DRAWINGS

The embodiments described herein will be understood more fully from the detailed description given below and from the accompanying drawings, which, however, should not be taken to limit the application to the specific embodiments, but are for explanation and understanding only.



FIG. 1 is a block diagram of an exemplary network architecture, in accordance with one embodiment of the present invention.



FIG. 2A is a block diagram of one embodiment of a client media manager.



FIG. 2B is a block diagram of one embodiment of a digital fingerprint manager.



FIG. 3 is a flow diagram showing an embodiment for a method of associating data with a digital fingerprint.



FIG. 4 is a flow diagram showing an embodiment for a method of replacing a digital fingerprint on a user device with a digital fingerprint of a master copy of a work.



FIG. 5 is a flow diagram showing an embodiment for a method of replacing a digital fingerprint on a user device based on the quality of a work during playback.



FIG. 6 is a flow diagram showing an embodiment for a method of subscribing to data associated with a work for display during playback by a client device.



FIG. 7 is a flow diagram showing an embodiment for a method of processing digital fingerprints and associated data received by a server.



FIG. 8 is a flow diagram showing an embodiment for a method of streaming media work to a client with associated data.



FIG. 9 is a flow diagram showing an embodiment for a method of processing client requests for data subscriptions by a server.



FIG. 10 illustrates a sequence diagram of transmission of digital fingerprints and data between a producer client, a server, and a consumer client, in accordance with one embodiment of the present invention.



FIG. 11 is a block diagram illustrating an exemplary computer system, in accordance with one embodiment of the present invention.





DETAILED DESCRIPTION OF THE PRESENT INVENTION

Methods and systems for enabling a user device to receive user-entered data (or other user originated data) and associate that data with a fingerprint of a segment for a work are described. Methods and systems for enabling a user device or server to transmit data associated with a fingerprint for playback are also described. The user device may be any content rendering device that includes a modem or network interface for connecting the user device to a network. Examples of such user devices include cellular telephones, personal digital assistants (PDAs), portable media players, installed media players, tablet computers, laptop computers, netbooks, televisions, smart TVs (televisions with integrated internet capabilities) cable and satellite television set-top boxes, smart glasses, smart clothing, smart watches, smart appliances, and the like.


In one embodiment, a user device plays a work and receives data to be associated with a particular point in the work. Alternatively, the user device may use a microphone and/or camera to sample a work from a surrounding environment (e.g., to sample a performance of a work or a work being rendered by another device). The user device may receive data to be associated with a particular point of the sampled work. A work may be anything that is fixed in a tangible medium. Some examples of works include, but are not limited to, audio renderings, video renderings, images and video/audio renderings. An example of an audio rendering is a song or other audio track. Examples of video renderings include animation or video sequence. Examples of an image include photographs and paintings. Examples of audio/video renderings include movies, television shows, cartoons, and any audio/video combination that is fixed using MPEG, AVI, VHS or any of the analog or digital encoding technologies as are commonly known. A single work may be rendered in many different ways in a tangible medium. For example, one fixed audio segment may be fixed on an analog tape, in an MP3 audio stream, and as part of a soundtrack in an audio/video rendering, and so forth. It will be obvious to anyone fluent in the art that embodiments of the present invention can apply to one entire work and to segments of a work. It will also be obvious that one work may contain segments of another work. Note that in some embodiments (e.g., in the case of sampling a live performance), the work being sampled may not initially be embodied in a tangible medium.


The user device may generate a user digital fingerprint of a segment of the work at the particular point in the work and associate the data to the fingerprint. As used herein, a user digital fingerprint may be a fingerprint of a work generated by a user device. The data and user digital fingerprint may be sent to a server to be saved for use during a later playback of the work. In one embodiment, the data and user fingerprint together form a tag. The server may replace the user digital fingerprint in the tag with a master digital fingerprint. As used herein, a master digital fingerprint may be a fingerprint of a high quality version of the known work. A second user device may receive the digital fingerprint and data at some point in time. The second user device may use the associated user fingerprint or master fingerprint to determine the point in the playback of the work that corresponds to the point that has data associated with it. The second user device may present the associated data to the user of the second user device. For example, a first user may use a mobile phone to play a video and enter text commentary at particular points in the video. A second user device, while playing back the same work, may identify the particular point in the video using the digital fingerprint, and may present the commentary entered by the first user at the particular point in the video.


In another embodiment a first device may be rendering a media stream. A second device may capture samples of the rendering by means of a microphone or camera on the second device. Data may be input by a user, and may be associated with a user fingerprint created from the captured samples of the media stream. For example the first device may be rendering a DVD or radio program. The second device may be sampling this media stream by way of a camera or microphone. The second device generates a user digital fingerprint of an immediate portion of the media stream being samples and associates the data with the user digital fingerprint for later use. In this example, the term immediate portion may mean a portion of the captured samples of the media stream (which may occur as much as two minutes before or two minutes after the point in the media stream where the data should be associated).


In another embodiment, both actions may occur on the same device instead of separate devices. A user device may play a work and receive data to be associated with a particular point in the work. The user device generates a user digital fingerprint of the work, or portion thereof, and associates the data to the user fingerprint. The data and user fingerprint (or master fingerprint) may be saved locally on the user device for use during a later playback of the work. During later playback of the work on the same device (which may be a same rendition of the work or a different rendition of the work), the user device may determine the point in the work that has associated data and present it to the user. For example, a user may download a video to a tablet computer, play it on the tablet computer, and enter text commentary at particular points in the video. The same tablet computer while playing back the video, may present the commentary entered by the first user at the particular point in the video.


In another embodiment the data associated with a point in the work using the fingerprint may instruct the client device to take some action. By means of example and not limitation, some actions include—communicating with another application on the device, such as a to-do list application; communicating with another server, such as one that would provide a purchase recommendation to the user; communicating with another server, such as one that would log the exposure of the device to the work at the point of the fingerprint; communicating with another device to cause it to behave in some way, such as vibrate, rotate, elevate, release a scent, change color, change temperature, emit sounds, and/or display some information; and so forth.


In another embodiment the user device may generate a user fingerprint from a media stream. The user device may use this fingerprint to identify the work being played. The user device may then download a master fingerprint of a known work which corresponds to the work being played. The user device then associates data with the master fingerprint of the known work. Note that in an alternative embodiment, the user device may extract a portion of the master fingerprint and associate the data with the extracted portion of the master fingerprint. For example, the master fingerprint may be a fingerprint of multiple segments. The user device may extract a portion of the master fingerprint that is associated with a particular segment or set of segments.



FIG. 1 is a block diagram of an exemplary network architecture 100 in which embodiments described herein may operate. The network architecture 100 may include a server system 140, a media server 150, and one or more user devices 105-110 capable of communicating with the server system 140 and/or the media server 150 via a network 135 (e.g., a public network such as the Internet or a private network such as a local area network (LAN)) and/or a wireless communication system 130. In one embodiment, a user device 105 connects to server system 140 and/or media server 150 via the wireless communications system 130 and network 135. In another embodiment a user device 110 connects to server system 140 and/or media server 150 via network 135. In another embodiment user device 105 is not connected to a network and performs the described functions in isolation.


The user devices 105-110 may be variously configured with different functionality to enable consumption of one or more types of media items and/or sampling of works from an environment in which the user devices 105-110 are placed. The media items may be any type of format of digital content, including, for example, digital audio (e.g., music, audible books, etc.), digital video (e.g., movies, television, short clips, etc.), and multimedia content. Each media item may include a specific work. The user devices 105-110 may include any type of content rendering devices such as mobile phones, laptop computers, portable media players, tablet computers, cameras, video cameras, netbooks, notebooks, desktop computers, televisions, cable and satellite television set-top boxes, audio or image sensing eyewear, and the like. In one embodiment, the user devices 105-110 are mobile devices. The user devices 105-110 may store content locally on storage media or in memory for later playback. Additionally, media server 150 may deliver media to the user devices 105-110, such as during streaming of music or videos to the user devices 105-110.


In one embodiment, user devices 105-110 may include a microphone 123 and/or a camera 124, which may be integrated into the device or attached externally. Microphone 123 may be used to sample audio of a surrounding environment of user devices 105-110. Similarly, Camera 124 may be used to sample audio, video, or images of a surrounding environment of the user device 105-110. For example, if a nearby media rendering device 175 (e.g., a radio having a radio receiver 178 or a television (TV) having a TV receiver 180, or a DVD player) is playing a work, the microphone may pick up segments of the work being played by the media rendering device 175.


In one embodiment, one or more of the user devices 105-110 include a client media manager 115. The client media manager 115 may manage the processing of media items on the user devices 105-110, the provisioning of sampled audio and/or video data that includes segments of works, as well as the generation of digital fingerprints of the work (or works) included in the media items. For example, the client media manager 115 may manage the generation of user digital fingerprints of audio, video, or images captured by user devices 105-100 via microphone 123 or camera 124 from the surrounding environment. The client media manager 115 may also manage the generation of user digital fingerprints directly from the media being rendered by playback module 122. The client media manager 115 may also manage the receipt of data, association of the data with the user digital fingerprints (e.g., to generate a tag), sending and receiving information (e.g., tags) to and from server system 140, and the presentation of data during playback of a work. The client media manager 115 may be comprised of a producer module 120 and a consumer module 125.


The producer module 120 may handle processing involved in the management of the data to be associated with a work played on or sampled by the user devices 105-110. In one embodiment, producer module 120 monitors playback of a work (e.g., a work included in a media item played on the user device or a work sampled from an environment by the user device), and generates user digital fingerprints of the work locally on the user devices 105-110. In one embodiment, a playback module 122 on the same user device 105-110 as the client media manager 115 plays the work that is fingerprinted. Alternatively, the user device 105-110 may not include a playback module 122, and may rely on sampling of a work from an environment of the user device 105-110. The work may be in streamed media being played by a player on the user device, such as a streamed movie or song being provided by a media server. The work may also be in a stored media item that is being played on the user device, such as playback of a digital video disk (DVD), stored movie file, stored audio file, and so forth. The work may also be a broadcast of the work that is received by a tuner on the user device. For example, the work may be a radio broadcast, a television broadcast, and so forth. The work may also be sampled from an environment of the user device. For example, the work may be rendered from any source by another device, the rendering of which is then sensed by the user device.


In one embodiment, digital fingerprints are generated continuously during playback. Alternatively, a cache of recently played segments of a work may be maintained, and fingerprints may be generated from such cached segments, present segments, and/or subsequent segments responsive to a user command to add data to the work at a particular point in the work. Producer module 120 receives a command to associate data with the work at a particular point in the work to be presented at the same point during playback of the work at a later time. For example, the data may be text commentary, a digital image, a uniform resource locator (URL), a video, a sound effect or a command.


Producer module 120 associates the received data with the user digital fingerprint that corresponds to the segment of the work at the particular point in the work and saves it for later use. In one embodiment, producer module 120 generates a tag that includes the user digital fingerprint and the data. A segment of a work may be less than an entirety of the work and may include at least one of audio or video or image media content. In one embodiment, a segment is a clip (e.g., a sequence of frames) of the work. For example, a segment may be between a single frame and a 10 second clip of a video or song. For example, a segment may be between 5% and 100% of an image. For example, a segment may contain the entire visual image and some irrelevant other data around the image, as when one takes a video of a television screen but the television screen does not consume the entire image space. In one embodiment, the data and associated user digital fingerprint are saved locally on user devices 105-110 for later use on the same user device. In another embodiment, the data and associated user digital fingerprint are transmitted to server system 140 to be saved in data storage 160 and fingerprint storage 155 for later use on the same or other user devices. The server system 140 may additionally replace the user digital fingerprint with a higher quality master digital fingerprint (or a portion of a higher quality master digital fingerprint). Such replacement may be particularly useful when the user fingerprint was generated from a segment of a work sampled from a microphone or camera.


The consumer module 125 may handle processing involved in presenting the data on the same or different user devices 105-110 during later playback of the same work. Said playback may occur on the same user device 105-110. Alternatively said playback rendering may occur on some other device and be sampled by microphone 123 or camera 124. During playback, consumer module 125 may generate fingerprints of segments of the work and compare the digital fingerprint of the segment of the work being played back to the user digital fingerprints or master fingerprints stored locally on the user devices 105-110. Alternatively, consumer module 125 may generate fingerprints and send these fingerprints to server system 140 for comparison to user fingerprints or master fingerprints. In such an embodiment, the server system may respond with data associated with a master fingerprint or user fingerprint matching the fingerprint that was sent to the server system. In one embodiment, segments may overlap. For example, a first segment may include seconds 1-5 in a video, a second segment may include seconds 2-6, a third segment may include seconds 3-7, and so on. Accordingly, consumer module 125 may generate a continuous stream of fingerprints from overlapping segments during playback. In one embodiment, fingerprints of segments are generated before those segments are played. This enables a match to be made to the stored fingerprint associated with the data before the segment associated with the data is played. Note that a match may be an approximate match. In one embodiment, two fingerprints are determined to match if they differ by less than a threshold amount (e.g., 10%, 20%, etc.).


Note that playback of the work may begin before the user device 105-110 has received any data or associated master fingerprints (or user fingerprints). In such an embodiment, consumer module 125 may query server system 140 for data and associated fingerprints after playback of the work by playback module 122 has begun, or before the rendering device 175 has begun rendering the work.


When consumer module 125 encounters a match between a generated digital fingerprint and a saved digital fingerprint that is associated with data, the data will be used. One use of the data is that it be presented to the user on the user devices 105-110. Another use is that the data be presented on another device such as a TV display or radio. Additionally, other actions may be performed, such as communicating with another device or server, communicating with another application on the user device, loading a web page, posting data to a blog or social media site, and so forth. One can imagine a user device posting to a user's Facebook page a message that the user has just watched some particular part of a movie or television show.


In one embodiment, a playback time range is associated with the digital fingerprint. The playback time range may indicate a point during playback at which digital fingerprints shall be generated for comparison to the saved fingerprint. This may save processing power by minimizing the number of fingerprints that are generated during playback. The playback time range may include a time in the work associated with the segment used to generate the fingerprint associated with the data plus or minus an error factor (e.g., 10 minutes). The error factor may account for changes that are made to the work (e.g., cutting the play time of the work to add commercials, changing a starting time of the work, and so forth).


In another embodiment, consumer module 125 may send a request to server 140 to subscribe to any data saved on the server system 140 that is entered by a particular user on any user device or any data saved for a particular work. During playback of a work, consumer module 125 may generate a digital fingerprint of the segment of the work being played back and send a request to server system 140 to determine whether there is any saved data associated with a master fingerprint or user fingerprint that matches the fingerprint generated on the user device. If server system 140 finds any saved data associated with a matching master or user fingerprint, it may then send that saved data to consumer module 125. When consumer module 125 encounters the particular point in the work where the fingerprint matches that of the master or user fingerprint associated with the data, the data will be used in any of the ways previously described.


Alternatively, consumer module 125 may send a request to server system 140 to receive all fingerprints with associated data for a particular work that have been generated by one or more entities to which the user subscribes. Server system 140 may then send the fingerprints and the associated data to the user device. Consumer module 125 may match the fingerprints with the generated fingerprints during playback and when the particular points in the work are encountered, use the associated data as appropriate.


In one embodiment, the data may be presented by displaying text associated with the particular point in the work. Additionally, the user devices 105-110 may display a digital image, launch a web browser to display a URL, play a video clip or sound effect, or execute a command on the user devices 105-110. Other types of data may also be associated with the fingerprint to perform other actions.


User devices 105-110 may connect to the server system 140 via a wireless communication system 130. The wireless communication system 130 may provide a wireless infrastructure that allows users to use the user devices 105-110 to consume items provided by the server system 140 without being tethered via hardwired links. The wireless communications systems 130 may be wireless fidelity (WiFi) hotspots connected with the network 135. The wireless communication systems 130 may alternatively be a wireless carrier system (e.g., as provided by Verizon®, AT&T®, T-Mobile®, etc.) that can be implemented using various data processing equipment, communication towers, etc.


The server system 140 may include one or more machines (e.g., one or more server computer systems, routers, gateways, etc.). In one embodiment, the server system 140 includes one or more cloud based servers (such as server systems made accessible to network connectivity via the internet or wireless carrier systems), which may be hosted, for example, by cloud based hosting services such as Amazon's® Elastic Compute Cloud® (EC2).


The server system 140 may have greater resources than the user devices 105-110. Accordingly, the server system 140 may implement resource intensive algorithms for matching the fingerprint of the work during playback to fingerprints associated with data for presentation on the user devices 105-110. Thus, in some instances improved throughput and/or improved fingerprint matching may be achieved by having the server system 140 perform fingerprint matching for the user devices 105-110.


In one embodiment, server system 140 may include a digital fingerprint manager 145, a fingerprint storage 155, and a data storage 160. Digital fingerprint manager 145 is configured to match user digital fingerprints generated by user devices 105-110 to master digital fingerprints of known works stored and to previously generated user digital fingerprints stored on the server system 140 in fingerprint storage 155. Additionally, digital fingerprint manager 145 manages the receipt, storage, and distribution of data associated with master digital fingerprints of known works and data associated with user digital fingerprints. Data received by digital fingerprint manager 145 is stored in data storage 160 for later distribution. Alternatively, master and/or user digital fingerprints and data may be stored together in a single file, or may be stored in a relational database. Further, digital fingerprint manager 145 processes subscription requests from user devices 105-110, utilizing fingerprint storage 155 and data storage 160.


For example, producer module 120 on user devices 105-110 may create a user fingerprint and associated data combination, then send the combination to server system 140 via network 135. Digital fingerprint manager 145 on server 140 will receive the user fingerprint and data combination, and compare the user fingerprint generated by the user device to the master fingerprints stored in fingerprint storage 155. Once a corresponding master fingerprint is located in fingerprint storage 155, digital fingerprint manager 145 may store the data in data storage 160 and associate that data with the master fingerprint of the known work stored in fingerprint storage 155. Thus, the data may be stored on the server system 140 such that it is associated with a high quality master digital fingerprint of the work. This may improve an ability to match future user fingerprints generated from the segments of a low quality of a work being sampled to the digital fingerprint associated with the data.


In one embodiment, if no match to a master fingerprint can be made, then digital fingerprint manager 145 may store the data in data storage 160, store the user digital fingerprint in fingerprint storage 155, and associate the two. Thus, it is possible that some elements of data in data storage 160 are only associated with user fingerprints and not with any master fingerprint. Alternatively, even if a match is made between a user fingerprint and a master fingerprint, the digital fingerprint manager 145 may choose to store the user digital fingerprint in fingerprint storage 155 and associate the data with both fingerprints. Thus, the digital fingerprint manager 145 may have several fingerprints associated with data. This multiplicity of fingerprints may be useful to improve the ability to match future user fingerprints.


In another embodiment, consumer module 125 on user devices 105-110 sends a subscription request for a media work that is saved on server system 140. The work may be downloaded and stored locally on user devices 105-110 or it may be streamed to the user devices 105-110 via media server 150, or it may be streamed to an ancillary media rendering device and captured via microphone 123 or camera 124. For works stored locally on user devices, digital fingerprint manager 145 may transmit some or all digital fingerprints of the work stored in fingerprint storage 155 along with associated data from data storage 160 to the user device so the user device can manage playback and presentation of the data locally.


For works streamed via media server 150, digital fingerprint manager 145 may transmit the fingerprints and associated data to media server 150 so that it may embed these in the media stream such that the user device need not compare locally generated digital fingerprints to those on the server. In this embodiment, media server 150 streams the work with the associated data already integrated at the appropriate place in the work. In one embodiment, media server 150 includes a fingerprint comparison module 185 and a data insertion module 188. The fingerprint comparison module 185 may generate fingerprints of a work being streamed, and may compare those fingerprints to a fingerprint received with associated data from server system 140. Once a match is identified, data insertion module 188 may insert the data into the work at a position in the work indicated by the matching fingerprints. Thus, media server 150 may stream both the data and the work to the user device 105, 110. Then the user device would not need to perform any fingerprint generation or comparison. The user device may simply act on the data when it is encountered in the stream.


In another embodiment the digital fingerprint manager 145 may transmit a master digital fingerprint of a known work from fingerprint storage 155 to the user devices where producer module 120 will make the comparison between the producer generated fingerprint and the master fingerprint of the known work. When the producer module 120 is instructed to create a tag it may associate the data for the tag with a master fingerprint taken from a portion of the fingerprint of the known work.



FIG. 2A is a block diagram of one embodiment of a client media manager 200, which may correspond to the client media manager 115 of FIG. 1. The client media manager 200 may include one or more of a producer module 205 and a consumer module 210. Additionally, client media manager 200 may receive an incoming media work 240, incoming digital fingerprints 241 and incoming data 242, as well as transmit outgoing digital fingerprints 243 and outgoing data 244. The incoming work 240 may be from a digital stream, a playback module 225, a microphone capture 250, a camera 255, or other sensor capable of fixing the work in a digital form. The incoming work 240 may be a sampling of a work being played on a separate device.


Producer module 205 is configured to enable a user device to associate data to a segment of a work at a particular point in the work. In one embodiment, producer module 205 includes a fingerprint generator 215, a data association module 220 and a data action module 230. In one embodiment, producer module 205 may correspond to the producer module 120 of FIG. 1.


Fingerprint generator 215 is configured to generate a digital fingerprint from a segment of a work, such as audio and/or video content. In one embodiment, fingerprint generator 215 may receive the audio and/or video content via incoming work 240. Fingerprint generator 215 may create the digital fingerprint using conventional digital signal processing known in the art. For example, a digital fingerprint of a sound stream may be generated according to acoustic and/or perceptual features over time. In one embodiment, digital fingerprints may be generated from the media content of a work according to a predetermined or user-defined interval. In another embodiment, a digital fingerprint may be generated when a user attempts to associate data with a segment of a work at a particular point in the work.


In one embodiment, digital fingerprints are generated by generating a feature vector of a segment of the work. The feature vector may be generated from an audio portion of the work, an image portion of the work, or both. For example, in one embodiment, fingerprint generator 215 measures a variety of acoustical features of a segment. The acoustical features may include loudness, pitch, bass, brightness, bandwidth, Mel-frequency cepstral coefficients (MFCCs), and so forth. Fingerprint generator 215 may also compute first and/or second derivatives of some or all of these features to determine changes in the features and rates of changes in the features. Fingerprint generator 215 may compute statistical measurements such as mean and standard deviations of each of these features over the segment as well. Some or all of these values may be included in the feature vector. For example, in one embodiment, fingerprint generator 215 measures a variety of visual features of a frame. The visual features may include luminosity, pixel colors, shading, etc. For example in one embodiment, fingerprint generator 215 measures the variation in visual features over the segment of the work. The time varying features may include the motion of pixels or pixel regions, the change in luminosity, the gross difference in pixel regions, and so forth.


An optional playback module 225 configured to render a work on the user device or otherwise play the work. In one embodiment, an audio file, video file, video stream, audio stream, etc. may be played by playback module 225. Playback module 225 may provide played (or to be played) segments of the work to client media manager 200. Alternatively, a microphone 250 and/or camera 255 may capture segments of a work from a surrounding environment, and may provide these segments of the work to client media manager 200.


Data association module 220 is configured to associate data with a segment of a work at a particular point in the work. In one embodiment, data association module 220 may be invoked by producer module 205 when a user issues a command to associate data with a work being played or sampled. For example, a user may watch a video and issue a command to enter text commentary at a particular point in the video. In another embodiment, data association module 220 may be invoked by producer module 205 when a user issues a command to associate data with a work being captured by a microphone 250. Data association module 220 may receive the user-entered data via a keyboard and associate the data with that point in the video. In one embodiment this data may be user generated commentary. In one embodiment, this association may be accomplished by utilizing the user fingerprint generated by fingerprint generator 215 for that segment of the work. In one embodiment data association module 220 matches the user fingerprint from fingerprint generator 215 to a master fingerprint (or a portion of a master fingerprint) of a known work and associates the data with the master fingerprint (or portion thereof) of the known work. Data association module 220 may save the data and associated fingerprint locally on the user device, either combined or separately in a file or database. Alternatively, the data and digital fingerprint may be sent to a server system via outgoing data 244 and outgoing digital fingerprints 243 respectively.


Data action module 230 may be configured to display data entered by a user during the process of associating that data with a work. In one embodiment, if a user issues a command to associate text commentary to a video, data action module 230 may present a window on the screen of the user device to allow the user to observe the text being entered. In an alternative embodiment, if a user issues a command to associate a sound file to a work, data action module 230 may present a graphical representation of a recording device to permit the user to start and stop the sound file recording. Thus, a user may review how generated data will be presented along with the work. In another embodiment, the user may perform a new work that is captured via a microphone or camera or both, and this new work may become the data associated with the user fingerprint.


Consumer module 210 is configured to enable a user device to receive and display data associated with segments of a work at particular points in the work. Consumer module 210 may also perform other actions at particular points in the work based on the data. In one embodiment, consumer module 210 includes a fingerprint generator 215, a fingerprint matching module 235, and a data action module 230. In one embodiment, consumer module 210 may correspond to the consumer module 125 of FIG. 1.


Fingerprint generator 215 is configured to generate a user digital fingerprint from a segment of a work, as described above. In one embodiment, fingerprint generator 215 may also generate user digital fingerprints during playback of a work in order to determine if and when associated data is to be presented to the user (or other actions are to be performed). For example, if a user plays a video after having subscribed to data and fingerprints entered by an entity for that particular video, fingerprint generator 215 may generate digital user fingerprints for the video during playback that will be used to compare to tag fingerprints (fingerprints associated with or included in a tag) to determine the particular point in the video to present the data. In one embodiment, the entity may be a user who enters data associated with a media work. For example, a user may associate text commentary data with particular points in a video work. In another embodiment, the entity may be an automated transcription service that associated data with a media work from a data store. For example, an automated service may add statistical information at particular points in a broadcast of an athletic event, such as historical batting averages of baseball players during the broadcast of a baseball game. Another example is an automated object recognition system associating data about a recognized object, such as a particular automobile, actor, location, or product, to particular points in the work.


Fingerprint matching module 235 is configured to match digital fingerprints of a work with stored user or master fingerprints associated with data in order to determine points in the work to present the data. In one embodiment, fingerprint matching module 235 receives digital fingerprints generated by fingerprint generator 215 in consumer module 210 from incoming work 240. In one embodiment, a user device may receive a collection of digital fingerprints with associated data for a particular video from a server and store them locally. This collection of fingerprints may contain user fingerprints from other users, user fingerprints from this user, and/or master fingerprints. During playback of that video, fingerprint matching module 235 may compare the fingerprints received from the server (e.g., fingerprints with associated data) to those fingerprints generated by fingerprint generator 215 (e.g., newly generated user fingerprints) in order to use the associated data at the appropriate point in the video. In another embodiment, a user device may receive a collection of fingerprints with associated data for a number of works and store them locally. In another embodiment, a user device may receive fingerprints with associated data for a number of works, all the data originating from a particular source.


Data action module 231 is configured to display data associated with a work at a particular point in the work and/or to perform other actions at the particular point in the work. In one embodiment, data action module 231 may receive a notification during playback of a work that there is data associated with a particular point in a segment of that work. Data action module 231 may then present the data on the user device at the appropriate point during playback. For example, during playback of a video, data action module 231 may receive notification from fingerprint matching module 235 that there is text commentary associated with a particular point in the video. Data action module 231 may then present a window on the screen of the user device to display the text commentary on the screen. Alternatively, data action module may perform other actions at the particular point in the video, such as loading a web page, loading an application, communicating with a remote device or server, and so forth.



FIG. 2B is a block diagram of one embodiment of a digital fingerprint manager 252, which may correspond to the digital fingerprint manager 145 of FIG. 1. The digital fingerprint manager 252 may include one or more of a fingerprint matching engine 258, a data management engine 260, a media quality analyzer 265, and a subscription manager 270. Additionally, digital fingerprint manager 252 may receive incoming digital fingerprints 275 and incoming data 280, as well as transmit outgoing digital fingerprints 285 and outgoing data 290.


Fingerprint matching engine 258 is configured to match user digital fingerprints generated by a user device with high quality master digital fingerprints of known works stored on a server system. For example, a user device that captures user digital fingerprints of a work in order to associate data with particular points in that work may send the user digital fingerprints to fingerprint matching engine 258 as part of the process to store the associated data on the server


Data management engine 260 is configured to store and distribute data entered by a user device associated with a work at a particular point in the work. Data may be stored in a storage facility such as data storage 160 from FIG. 1. In one embodiment, data management engine 260 receives incoming data 280 in combination with incoming user digital fingerprints 275. Once the incoming user digital fingerprints 275 are matched with master digital fingerprints of known works via fingerprint matching engine 258, the incoming data 280 may be stored on the server and associated with the master digital fingerprints of the known work. In another embodiment, when a user device subscribes to data of a known work, data management engine 260 is invoked to query the data storage and transmit outgoing data 290 to the user device. In another embodiment the user device requests a master fingerprint from the data management engine, does the matching on the user device, potentially extracts an appropriate portion of the master fingerprint, and returns that to the data management engine with the data.


Media quality analyzer 265 is configured to analyze the quality of media being played back on the user device. Such an analysis may be made based on the incoming user digital fingerprints 275 received from the user device. In one embodiment, media quality may be analyzed using objective audio and video techniques known in the art such as signal-to-noise ratio (SNR) or peak signal-to-noise ratio (PSNR). Media quality analyzer 265 may also examine an audio or video work for the presence of network transmission artifacts during playback when compared to a master copy to determine whether the transmitted signal has been degraded. In one embodiment, a received fingerprint includes an associated media quality value that may have been generated by a producer module that generated the fingerprint. The producer module may have generated the media quality value using the above described techniques.


Alternatively, media quality analyzer 265 may determine the media quality from the digital fingerprint itself. For example the producer module may determine that the user fingerprint matches poorly with a master fingerprint thus indicating that the user fingerprint was generated from a poor quality rendering of the original work or that substantial noise was included in the sampling of the work from a microphone or camera. The producer module may determine that the digital user fingerprint matches in some segments but not in others. The producer module may infer that the user fingerprint was generated from a rendering that included pauses, or that failed to render some sections of the original work.


The incoming user fingerprints may be replaced in the outgoing digital fingerprint with the master fingerprints stored on the server for the particular segment of the work. Media quality analyzer 265 may thus lower network traffic and limit processing when the work being played back is known to be a higher quality sample such as a movie stored locally on the device or being streamed via a high speed broadband connection. Additionally, replacing fingerprints determined to be degraded may improve performance when matching against the same work in future playbacks. Alternatively, the fingerprint may be replaced with the corresponding fingerprint of the master copy of the work regardless of the media quality.


Subscription manager 270 is configured to process subscription requests from user devices. In one embodiment, a user device sends a request to the server to receive all data and associated fingerprints entered for a particular work or by a particular entity. In one embodiment, the entity may be a user who enters data associated with a media work. For example, a user may associate commentary data with particular points in a video work. In another embodiment, the entity may be an automated transcription service that associated data with a media work from a data store. For example, an automated service may add statistical information at particular points in a broadcast of an athletic event, such as historical batting averages of baseball players during the broadcast of a baseball game. As another example, an automated service may add purchase information for items that are shown in a particular scene of a television show. As another example, an automated service may add travel information for a location mentioned in a song. Subscription manager 270 receives this request, and operates in conjunction with fingerprint matching engine 258 and data management engine 260 to transmit the data and fingerprints associated with a work to user devices of subscribing users.



FIG. 3 is a flow diagram of an embodiment for a method 300 of associating data with a digital fingerprint. Method 300 is performed by processing logic that may comprise hardware (circuitry, dedicated logic, etc.), software (such as is run on a general purpose computer system or a dedicated machine), or a combination of both. In one embodiment, the method 300 is performed by a user device 105-110 of FIG. 1. For example, the method of FIG. 3 may be performed by a client media manager of a user device.


At block 305 of method 300, processing logic begins sampling of a work on a computing device. In one embodiment, the sampling may be of a media file or stream playing back on the device itself. In another embodiment, the sampling may be of a work being played on another device directly coupled to the computing device. In another embodiment, the sampling may be an audio and/or video sampling of the environment of the user device using a microphone or camera coupled to or contained within the user device. The sampling may capture segments of the work. In one embodiment, the computing device may be a personal computer. In an alternative embodiment, the computing device may be a tablet computer, smartphone, PDA, smart TV, smart eyewear, or the like on which media can be played or sampled. In an example, a television or radio or Internet broadcast may be played by a TV or radio, and a microphone or video camera coupled to the computing device may pick up the played TV or radio broadcast.


At block 310, processing logic receives a command to associate data with the work being played at a particular point in the work. In one embodiment the point in the work is specified by the user indicating that the data should be associated with the point in the work that has just been rendered. In one embodiment, the data may represent text commentary manually entered by the user via a keyboard. In an alternative embodiment, the data may be a uniform resource locator (URL), a video, a sound effect, or a command. In another embodiment the data may be a new work created by the user, such as a video, a drawing, or a bit of audio commentary. Other types of data are also envisioned. At block 315, processing logic generates a user digital fingerprint of the segment of the work associated with the particular point in the work identified at block 310. At block 320, processing logic associates the data created at block 310 with the user digital fingerprint generated at block 315. This may include generating a single file that contains both the data and fingerprint. Alternatively, the data and fingerprint may be generated and stored separately and connected logically using a reference link or digital pointer (such as a hyperlink).


At block 325, processing logic transmits the user digital fingerprint and associated data to a server system, which may be, for example, a cloud based server and/or a server provided by a wireless carrier. The server may then store the user digital fingerprint and associated data on the server system. In one embodiment, the server may store the digital fingerprint and associated data together in a single record of a relational database. In another embodiment, the server system may store the digital fingerprint and associated data separately, such as in fingerprint storage 155 and data storage 160 from FIG. 1 respectively.



FIG. 4 is a flow diagram showing an embodiment for a method 400 of replacing a user digital fingerprint on a user device with a master digital fingerprint of a master copy of a work. Method 400 is performed by processing logic that may comprise hardware (circuitry, dedicated logic, etc.), software (such as is run on a general purpose computer system or a dedicated machine), or a combination of both. In one embodiment, the method 400 is performed by a user device 105-110 of FIG. 1. For example, the method of FIG. 4 may be performed by a client media manager of a user device.


At block 405 of method 400, processing logic generates a user digital fingerprint of a segment of a work that corresponds to a particular point in the work and associates data with the user fingerprint. At block 410, processing logic queries a server with the user digital fingerprint generated in block 405. The server system may analyze a quality of the user digital fingerprint and if found not to meet a predetermined threshold, send a replacement master digital fingerprint to the user device. In one embodiment, the server may do so from media quality analyzer 265 in FIG. 2B. At block 415, processing logic receives a master digital fingerprint from the server. At block 420, processing logic replaces the user digital fingerprint generated in block 405 with the new master digital fingerprint received from the server in block 415.


In one embodiment, a user may play or sample a work on a user device, and enter data associated with that work to be replayed at a later time on that same user device or a different user device. In this embodiment, the user device may be streaming a video from an online source where playback quality is low, thereby resulting in a low quality user digital fingerprint generated on the user device. In another embodiment, the user device may be sampling the rendered work via a microphone or camera, thereby resulting in a sample of media contaminated by environmental noise. The user device may query a server to obtain a higher quality master digital fingerprint of the work from a database of fingerprints of known works to replace the generated user fingerprint in order to prevent possible problems during later playback.



FIG. 5 is a flow diagram showing an embodiment for a method 500 of replacing a user digital fingerprint on a user device based on the quality of a work during playback or sampling. Method 500 is performed by processing logic that may comprise hardware (circuitry, dedicated logic, etc.), software (such as is run on a general purpose computer system or a dedicated machine), or a combination of both. In one embodiment, the method 500 is performed by a user device 105-110 of FIG. 1. For example, the method of FIG. 5 may be performed by a client media manager of a user device.


At block 505 of method 500, processing logic begins sampling or playback of a work by a user device. At block 510, processing logic generates a user digital fingerprint of a segment of the work at a particular point in the work and associates data with the fingerprint. At block 515, processing logic analyzes the quality of the segment of the work processed in block 510. At block 520, processing logic determines whether the quality of the segment of the work analyzed at block 515 satisfies a predetermined threshold. For example, a threshold may be set for video quality limiting the number of frames that can be dropped due to online bandwidth limitations. Additionally, a threshold may be set for an audio track that limits the amount of audio noise encountered during the playback of the segment.


If at block 520 processing logic determines that the segment quality meets the threshold, the method continues to block 535, and processing logic stores the user digital fingerprint. If not, the method continues to block 525, and processing logic queries a server for a replacement fingerprint. The query may include a copy of the generated user digital fingerprint. At block 530, processing logic receives a replacement fingerprint generated from a higher quality segment stored on the server system. At block 530 the received replacement fingerprint may be a master fingerprint of a known work or a higher quality user fingerprint.


At block 535, processing logic stores the digital fingerprint on the user device. If a replacement fingerprint was received by the server based on the threshold analysis conducted at block 520, the replacement is stored. Otherwise, the original user fingerprint is stored. The method may repeat continuously so long as a work is being played and data is being entered on the user device.



FIG. 6 is a flow diagram showing an embodiment for a method 600 of subscribing to data associated with a work for display during playback by a client device. Method 600 is performed by processing logic that may comprise hardware (circuitry, dedicated logic, etc.), software (such as is run on a general purpose computer system or a dedicated machine), or a combination of both. In one embodiment, the method 600 is performed by a user device 105-110 of FIG. 1. For example, the method of FIG. 6 may be performed by a client media manager of a user device.


At block 605 of method 600, processing logic subscribes to data provided by another entity. In one embodiment, the entity may be a user who enters data associated with a media work. For example, a user may associate text commentary data with particular points in a video work. In another embodiment, the entity may be an automated transcription service that associated data with a media work from a data store. For example a user may subscribe to all data entered by some particular user. For example a user may subscribe to all data entered by some particular transcription service. For example a user may subscribe to all data entered by any entity for a particular work.


In another embodiment, tags may be categorized, and processing logic may request all tags of a particular category that is associated with any work. For example, a user may subscribe to tags that that have been categorized as being associated with a particular celebrity, animal, science, politics, or other subject matter. These categories may be indicated by a user who generates the data. Alternatively, the data may be categorized using an automated categorization process or through a human mediated editorial process. Automated categorization may be performed by parsing data and analyzing it using one or more categorization rules. Each categorization rule may search for specific terms, words, phrases, etc. If such information is found, the rule may cause the data to be categorized with a category associated with that rule.


At block 610, processing logic receives data and associated fingerprints from a server. In one embodiment, a user device may receive all data and fingerprints for a particular work generated by the entity to which the user device is subscribed so that they may be stored on the user device prior to playback. For example, a user that intends to play a particular movie on a device may download all data and associated fingerprints from the server prior to playback in order to improve operating efficiency and reduce the risk of issues arising during transmission during playback. In another embodiment the device uses a user fingerprint to identify the work that is being sampled and downloads tags associated with the work.


At block 615, processing logic begins sampling of the work on the user device. At block 620, processing logic identifies a point in the work using the digital fingerprint that is associated with data received from the server. This may be performed by generating a sequence of overlapping digital fingerprints of the work during playback of the work. These digital fingerprints may be compared to the digital fingerprint associated with the data. If a matching digital fingerprint is found, the data may be used when the segment that was used to generate the matching fingerprint is played. For example, during the playback of a video on a device, processing logic may identify a particular point in the video where a prior user had associated text commentary. In another embodiment, during the viewing of a television show, processing logic may identify a particular point in the show where a URL should be displayed. At block 625, processing logic uses the data during playback of the particular point in the work. In one embodiment, if a prior user had entered text commentary regarding the particular point in the work, processing logic would display that commentary on the user device such that it is viewable by the user. In another embodiment, if a prior user had entered a video regarding the particular point in the work, processing logic would display that video on the user device such that it is viewable by the user. This presentation may consume the entire display surface. Alternatively this presentation may take place in a window consuming only a portion of the display surface. Alternatively the featured presentation may be reduced to a window consuming only a portion of the display surface and the presentation may consume the rest of the surface. Alternatively the presentation may be audio and play without consuming any of the visual display surface. Alternatively the featured presentation may pause while the prior user's video and audio is played. Alternatively the presentation may be made on another device, operatively coupled to the user device. Alternatively the user device may command another device to begin the presentation. As discussed above, other actions may also be performed based on the data at the particular point in the work.



FIG. 7 is a flow diagram showing an embodiment for a method 700 of processing digital fingerprints and associated data received by a server. Method 700 is performed by processing logic that may comprise hardware (circuitry, dedicated logic, etc.), software (such as is run on a general purpose computer system or a dedicated machine), or a combination of both. In one embodiment, the method 700 is performed by a server system 140 of FIG. 1. For example, the method of FIG. 7 may be performed by a digital fingerprint manager of a server system.


At block 705 of method 700, processing logic receives a digital fingerprint and associated data from a user device. At block 710, processing logic compares the user digital fingerprint received to a collection of master digital known work fingerprints stored on the server system such as in fingerprint storage 155 of FIG. 1. At block 715, processing logic identifies an additional fingerprint from the collection of master fingerprints of known works or some portion thereof that approximately matches the user digital fingerprint received at block 705. A person skilled in the art will recognize that there are a plethora of digital fingerprint techniques available to perform this matching. In one embodiment, the method may identify fingerprints matching known works such as movies, songs, episodic video, user generated video, speeches, paintings, photographs, or the like.


At block 720, processing logic associates the data received with the matching master digital fingerprint stored on the server. In one embodiment, the associated data may be located in the same data store record as the stored digital fingerprint. In another embodiment, the associated data may be referenced by the stored digital fingerprint via a pointer or other linking mechanism known in the art such that the associated data and digital fingerprint need not be in the same storage media. At block 725, processing logic stores the associated data for later presentation during media playback. In one embodiment, the associated data may be stored on the server system in data storage 160 of FIG. 1.



FIG. 8 is a flow diagram showing an embodiment for an optional method 800 of streaming media work to a client with associated data. Method 800 is performed by processing logic that may comprise hardware (circuitry, dedicated logic, etc.), software (such as is run on a general purpose computer system or a dedicated machine), or a combination of both. In one embodiment, the method 800 is performed by a server system 140 of FIG. 1. For example, the method of FIG. 8 may be performed by a media server of a server system.


At block 805 of method 800, processing logic receives a request from a client to stream a known work. In one embodiment, a client may be a playback module 122 that executes on a user device 105-110 of FIG. 1. For example, the client may be a personal computer, tablet computer, smart phone, smart eyewear, or other computing device. Since server systems generally possess more processing power than client devices, the processing used to determine the particular point in a work to present associated data may be conducted by the server and streamed to the client such that the client need only display the contents of the stream without further intervention. This method allows for client devices with limited processing resources to receive associated data at the proper point in the playback of a work.


At block 810, processing logic streams the known work to the client. It is understood that the method may utilize streaming technologies and known network protocols known in the art to transmit the media to the client across a network. In one embodiment, the method may access a media server such as media server 150 of FIG. 1 to stream the media to the client via network 135 of FIG. 1.


At block 815, processing logic generates a user fingerprint of the streamed work. At block 820, processing logic compares the user digital fingerprint generated at block 815 to fingerprints associated with stored data. At block 825, processing logic determines whether the generated user fingerprint matches a stored fingerprint associated with the data. If so, the method continues to block 830. Otherwise, the method proceeds to block 840,


At block 830, processing logic determines the point in the known work to insert data associated with the matching fingerprint. At block 835, processing logic sends the associated data to the client for presentation at the point in the known work. In one embodiment, the method may send the associated data embedded in the work as part of a single stream of data. In another embodiment, the method may establish two connections, ports, or “threads” with the client device sending the work and the associated data separately to be received by the client application. The client may simply present the work and the data without performing any additional processing to determine where to insert the data. At block 840, processing logic determines whether the work is still being streamed. If so, the method returns to block 815. Otherwise, the method ends.



FIG. 9 is a flow diagram showing an embodiment for a method 900 of processing client requests for data subscriptions by a server. Method 900 is performed by processing logic that may comprise hardware (circuitry, dedicated logic, etc.), software (such as is run on a general purpose computer system or a dedicated machine), or a combination of both. In one embodiment, the method 900 is performed by a server system 140 of FIG. 1. For example, the method of FIG. 9 may be performed by a subscription manager 220 of FIG. 2B.


At block 905 of method 900, processing logic receives a request from a client to subscribe to data provided by an entity. Alternatively, the request may be to subscribe to data having a particular categorization. At block 910, processing logic identifies a work to be played by the client. In one embodiment, processing logic may receive a digital fingerprint from a client to identify the work. In another embodiment, processing logic may receive the identity of the work (e.g., as part of the subscription request received at block 905). For example, processing logic may receive a request from a client to subscribe to all commentary for a specific video work.


At block 915, processing logic identifies data associated with the work. In one embodiment, the method may identify this information by utilizing data storage 160 of FIG. 1. At block 920, processing logic transmits the data and an associated fingerprint to the requesting client for use. In one embodiment, the method may transmit all data and fingerprints for the work to the client such that the client can store the information and use the data when the work is played back or sampled at some later time. In an alternative embodiment, the method may transmit the data as the work is being played back on the client. In another embodiment, the method may transmit all data and fingerprints from a particular user to the subscribing client such that the client can store the information and make use of it whenever the work is played or sampled.



FIG. 10 illustrates a sequence diagram of an example transmission of digital fingerprints and data between a producer client 1005, a server 1010, and a consumer client 1015, in accordance with one embodiment of the present invention. In one embodiment, producer client 1005 and/or consumer client 1015 may be user devices 105-110 of FIG. 1. In one embodiment, producer client 1005 and consumer client 1015 may logically represent the same physical device. In one embodiment, server 1010 may be server system 140 of FIG. 1.


At block 1020, the producer client 1005 generates a user fingerprint of a segment of a work and associates data with the fingerprint. Producer client 1005 then executes processing logic to send the user fingerprint and data to server 1025. At block 1030, the server associates the data and user fingerprint received with a known work fingerprint of a known work. The data is then stored on the server system. In one embodiment, the data is stored in data storage 160 of FIG. 1.


At block 1035, the server identifies a data subscription to the data stored at block 1030. The server then executes processing logic to send fingerprint and data to client 1040. Consumer client 1015 receives the fingerprint and data and begins sampling a media stream (or playback of a work) at block 1045. At block 1050, consumer client 1015 determines a point in the work to present the associated data. At block 1055, consumer client 1015 presents the data at the particular point in the work.


Note that the above embodiments have been described with reference to recorded works. However, embodiments of the present invention may additionally be applied to live video recordings. For example, a user may include a video camera that records a scene at a particular location (e.g., at Alcatraz island). The video camera may additionally include a display that presents the image being recorded. In one embodiment, the user may add data to the generated video recording, which may be sent to a server along with an associated fingerprint. When another individual takes an image of the same scene, his video camera may receive the data, and may present the data previously entered by the first user when the scene is detected. In one embodiment, a geo-location is associated with the data and fingerprint. When a user device determines that it is at that geo-location, it may retrieve data that has been recorded by other users at that geo-location.



FIG. 11 is a block diagram illustrating an exemplary computer system 1100 configured to perform any one or more of the methodologies performed herein. In one embodiment, the computer system 1100 corresponds to a user device 105-110 of FIG. 1. For example, computer system 1100 may be any type of computing device such as a PDA, a mobile phone, a laptop computer, a portable media player, a tablet computer, a camera, a video camera, a netbook, a desktop computer, a gaming console, a DVD player, a computing pad, a media center, and the like. Computer system 1100 may also correspond to one or more devices of the server system 140 of FIG. 1. For example, computer system 100 may be a rackmount server, a desktop computer, a network router, switch or bridge, or any other computing device. The computer system 1100 may operate in the capacity of a server or a client machine in client-server network environment, or as a peer machine in a peer-to-peer (or distributed) network environment. Further, while only a single machine is illustrated, the computer system 1100 shall also be taken to include any collection of machines that individually or jointly execute a set (or multiple sets) of instructions to perform any one or more of the methodologies discussed herein.


The computer system 1100 includes one or more processing devices 1135, which may include general-purpose processing devices such as central processing units (CPUs), microcontrollers, microprocessors, systems on a chip (SoC), or the like. The processing devices 1135 may further include field programmable gate arrays, dedicated chipsets, application specific integrated circuits (ASIC), a field programmable gate arrays (FPGA), digital signal processors (DSP), network processors, or the like. The computer system 1100 also includes system memory 1105, which may correspond to any combination of volatile and/or non-volatile storage mechanisms. The system memory 1105 stores information which may provide an operating system component 1110, various program modules 1115 such as digital fingerprint manager 1185, program data 1120, and/or other components. The computer system 1100 may perform functions by using the processing device(s) 1135 to execute instructions provided by the system memory 1105. Such instructions may be provided as software or firmware. Alternatively, or additionally, the processing device(s) 1135 may include hardwired instruction sets (e.g., for performing functionality of the digital fingerprint manager 1185). The processing device 1135, system memory 1105 and additional components may communicate via a bus 1180.


The computer system 1100 also includes a data storage device 1125 that may be composed of one or more types of removable storage and/or one or more types of non-removable storage. The data storage device 1125 includes a computer-readable storage medium 1130 on which is stored one or more sets of instructions embodying any one or more of the methodologies or functions described herein. As shown, instructions for the digital fingerprint manager 1185 may reside, completely or at least partially, within the computer readable storage medium 1130, system memory 1105 and/or within the processing device(s) 1135 during execution thereof by the computer system 1100, the system memory 1105 and the processing device(s) 1135 also constituting computer-readable media. While the computer-readable storage medium 1130 is shown in an exemplary embodiment to be a single medium, the term “computer-readable storage medium” should be taken to include a single medium or multiple media (e.g., a centralized or distributed database, and/or associated caches and servers) that store the one or more sets of instructions. The term “computer-readable storage medium” shall also be taken to include any medium that is capable of storing or encoding a set of instructions for execution by the machine and that cause the machine to perform any one or more of the methodologies of the present disclosure. The term “computer-readable storage medium” shall accordingly be taken to include, but not be limited to, solid-state memories, optical media, and magnetic media.


The computer system 1100 may also include one or more input devices 1140 (keyboard, mouse device, specialized selection keys, etc.) and one or more output devices 1145 (displays, printers, audio output mechanisms, etc.). In one embodiment, the computer system 1100 is a user device that includes one or more microphones 1150 and one or more speakers 1155.


The computer system may additionally include a wireless modem 1160 to allow the computer system 1100 to communicate via a wireless network (e.g., such as provided by a wireless communication system) with other computing devices, such as remote user devices, a server system, and so forth. The wireless modem 1160 allows the computer system 1100 to handle both voice and non-voice communications (such as communications for text messages, multimedia messages, media downloads, web browsing, etc.) with a wireless communication system. The wireless modem 1160 may provide network connectivity using any type of mobile network technology including, for example, cellular digital packet data (CDPD), general packet radio service (GPRS), enhanced data rates for GSM evolution (EDGE), universal mobile telecommunications system (UMTS), 1 times radio transmission technology (1×RTT), evaluation data optimized (EVDO), high-speed down-link packet access (HSDPA), WiFi, long term evolution (LTE), worldwide interoperability for microwave access (WiMAX), etc.


Computer system 1100 may additionally include a network interface device 1175 such as a network interface card (NIC) to connect to a network.


In the above description, numerous details are set forth. It will be apparent, however, to one of ordinary skill in the art having the benefit of this disclosure, that embodiments of the invention may be practiced without these specific details. In some instances, well-known structures and devices are shown in block diagram form, rather than in detail, in order to avoid obscuring the description.


Some portions of the detailed description are presented in terms of algorithms and symbolic representations of operations on data bits within a computer memory. These algorithmic descriptions and representations are the means used by those skilled in the data processing arts to most effectively convey the substance of their work to others skilled in the art. An algorithm is here, and generally, conceived to be a self-consistent sequence of steps leading to a desired result. The steps are those requiring physical manipulations of physical quantities. Usually, though not necessarily, these quantities take the form of electrical or magnetic signals capable of being stored, transferred, combined, compared, and otherwise manipulated. It has proven convenient at times, principally for reasons of common usage, to refer to these signals as bits, values, elements, symbols, characters, terms, numbers, or the like.


It should be borne in mind, however, that all of these and similar terms are to be associated with the appropriate physical quantities and are merely convenient labels applied to these quantities. Unless specifically stated otherwise as apparent from the above discussion, it is appreciated that throughout the description, discussions utilizing terms such as “receiving”, “generating”, “associating”, “querying”, “analyzing”, “replacing” or the like, refer to the actions and processes of a computer system, or similar electronic computing device, that manipulates and transforms data represented as physical (e.g., electronic) quantities within the computer system's registers and memories into other data similarly represented as physical quantities within the computer system memories or registers or other such information storage, transmission or display devices.


Some portions of the detailed description are presented in terms of methods. These methods may be performed by processing logic that may comprise hardware (circuitry, dedicated logic, etc.), software (such as is run on a general purpose computer system or a dedicated machine), or a combination of both. In certain embodiments, the methods are performed by a user device, such as user devices 105-110 of FIG. 1. In other embodiments, the methods are performed by server devices, such as server system 140 of FIG. 1.


Embodiments of the invention also relate to an apparatus for performing the operations herein. This apparatus may be specially constructed for the required purposes, or it may comprise a general purpose computer selectively activated or reconfigured by a computer program stored in the computer. Such a computer program may be stored in a computer readable storage medium, such as, but not limited to, any type of disk including floppy disks, optical disks, CD-ROMs, and magnetic-optical disks, read-only memories (ROMs), random access memories (RAMs), EPROMs, EEPROMs, magnetic or optical cards, or any type of media suitable for storing electronic instructions.


It is to be understood that the above description is intended to be illustrative, and not restrictive. Many other embodiments will be apparent to those of skill in the art upon reading and understanding the above description. The scope of the invention should, therefore, be determined with reference to the appended claims, along with the full scope of equivalents to which such claims are entitled.

Claims
  • 1. A method comprising: during sampling or a first playback of a work, receiving, by a user device, a command to associate data with the work at a segment of the work occurring at a particular point in time in the work;generating, by the user device, a user digital fingerprint of the segment of the work, wherein the segment comprises at least one of a sequence of frames of the work or adjacent in time samples of the work that begin at the particular point in time in the work, and wherein the user digital fingerprint comprises a feature vector of the segment of the work generated by the user device; andassociating the data with the user digital fingerprint, wherein the user digital fingerprint associated with the data will cause at least one of the user device or an additional user device to identify the segment of the work at the particular point in time in the work or an additional point in time in the work during a subsequent playback of the work and to present the data during the subsequent playback of the segment at the particular point in time or the additional point in time in the work.
  • 2. The method of claim 1, wherein said data comprises at least one of a text commentary, a digital image, a uniform resource locator (URL), a video, a sound effect, or a command.
  • 3. The method of claim 1, wherein the work is one of an audio rendering, a video rendering, or a video/audio rendering.
  • 4. The method of claim 1, further comprising: sending a query to a server, the query comprising the user digital fingerprint;receiving a master digital fingerprint of a segment of a copy of the work from the server, the segment of the copy corresponding to the segment of the work, wherein the master digital fingerprint is a digital fingerprint from a high quality version of the work that comprises a feature vector of the high quality version of the work; andreplacing the user digital fingerprint with the master digital fingerprint.
  • 5. The method of claim 4, further comprising: performing an analysis of a quality of the segment of the work based on at least one of characteristics of the segment or characteristics of the user digital fingerprint; andquerying the server in response to determining, based on the analysis, that the quality of the segment of the work fails to satisfy a quality threshold.
  • 6. The method of claim 1, further comprising: associating a playback time range with the user digital fingerprint, wherein the playback time range indicates a range of points in time during the subsequent playback at which to generate digital fingerprints for comparison with the user digital fingerprint.
  • 7. The method of claim 1, wherein during the subsequent playback of the work by the user device or the additional user device, the user device or the additional user device is to: generate a plurality of additional digital fingerprints of the work;identify an approximate match between one of the plurality of additional digital fingerprints and the user digital fingerprint or a master digital fingerprint corresponding to the user digital fingerprint;determine the particular point in time or the additional point in time of the work associated with the additional digital fingerprint that matches the user digital fingerprint or the master digital fingerprint; andpresent the data at the particular point in time or the additional point in time in the work, wherein the master digital fingerprint is a digital fingerprint generated from a high quality version of the work.
  • 8. The method of claim 1, wherein associating the data with the user digital fingerprint comprises generating a tag comprising the user digital fingerprint and the data.
  • 9. A system comprising: a first user device comprising a first memory and a first processing device operatively coupled to the first memory, wherein the first user device is to:during sampling or a first playback of a work, receive a command to associate data with the work at a segment of the work occurring at a particular point in time in the work;generate a user digital fingerprint of the segment of the work, wherein the segment comprises at least one of a sequence of frames of the work or adjacent in time samples of the work that begin at the particular point in time in the work, and wherein the user digital fingerprint comprises a feature vector of the segment of the work generated by the first user device; andassociate the data with the user digital fingerprint, wherein the user digital fingerprint associated with the data will cause at least one of the first user device or an additional user device to identify the segment of the work at the particular point in time in the work or an additional point in time in the work during a subsequent playback of the work and to present the data during the subsequent playback of the segment at the particular point in time or the additional point in time in the work.
  • 10. The system of claim 9, wherein the work is one of an audio rendering, a video rendering, or a video/audio rendering.
  • 11. The system of claim 9, further comprising: a second user device comprising a second memory and a second processing device operatively coupled to the second memory, wherein the second user device is to:receive the data and the user digital fingerprint or a master digital fingerprint corresponding to the user digital fingerprint;initiate the subsequent playback of the work; andperform the following during the subsequent playback of the work: generate a plurality of additional digital fingerprints of the work;identify an approximate match between one of the plurality of additional digital fingerprints and the user digital fingerprint or the master digital fingerprint corresponding to the user digital fingerprint;determine the particular point in time or the additional point in time in the work associated with the additional digital fingerprint that matches the user digital fingerprint or the master digital fingerprint; andpresent the data at the particular point in time or the additional point in time in the work, wherein the master digital fingerprint is a digital fingerprint generated from a high quality version of the work.
  • 12. The system of claim 9, wherein the first user device is further to: initiate the subsequent playback of the work; andperform the following during the subsequent playback of the work: generate a plurality of additional digital fingerprints of the work;identify an approximate match between one of the plurality of additional digital fingerprints and the user digital fingerprint or a master digital fingerprint corresponding to the user digital fingerprint;determine the particular point in time or the additional point in time in the work associated with the additional digital fingerprint that matches the user digital fingerprint or the master digital fingerprint; andpresent the data at the particular point in time or the additional point in time in the work, wherein the master digital fingerprint is a digital fingerprint generated from a high quality version of the work.
  • 13. The system of claim 9, wherein said data comprises at least one of a text commentary, a digital image, a uniform resource locator (URL), a video, a sound effect, or a command.
  • 14. The system of claim 9, wherein the first user device is further to: query a server, the query comprising the user digital fingerprint;receive a master digital fingerprint of a segment of a copy of the work from the server, the segment of the copy corresponding to the segment of the work, wherein the master digital fingerprint is a digital fingerprint from a high quality version of the work that comprises a feature vector of the high quality version of the work; andreplace the user digital fingerprint with the master digital fingerprint.
  • 15. The system of claim 14, wherein the first user device is further to: perform an analysis of a quality of the segment of the work based on at least one of characteristics of the segment or characteristics of the user digital fingerprint; andquery the server in response to determining, based on the analysis, that the quality of the segment of the work fails to satisfy a quality threshold.
  • 16. The system of claim 9, wherein the first user device is further to: associate a playback time range with the user digital fingerprint, wherein the playback time range indicates a range of points in time during the subsequent playback at which to generate digital fingerprints for comparison with the user digital fingerprint.
  • 17. The system of claim 9, wherein to associate the data with the user digital fingerprint the first user device generates a tag comprising the user digital fingerprint and the data.
  • 18. A computer readable storage medium comprising instructions that, when executed by a processing device, cause the processing device to perform operations comprising: during sampling or a first playback of a work, receiving, by the processing device, a command to associate data with the work at a segment of the work occurring at a particular point in time in the work;generating, by the processing device, a user digital fingerprint of the segment of the work, wherein the segment comprises at least one of a sequence of frames of the work or adjacent in time samples of the work that begin at the particular point in time in the work, and wherein the user digital fingerprint comprises a feature vector of the segment of the work generated by the processing device; andassociating the data with the user digital fingerprint, wherein the user digital fingerprint associated with the data will cause at least one of the processing device or an additional processing device to identify the segment of the work at the particular point in time in the work or an additional point in time in the work during a subsequent playback of the work and to present the data during the subsequent playback of the segment at the particular point in time or the additional point in time in the work.
  • 19. The computer readable storage medium of claim 18, the operations further comprising: sending a query to a server, the query comprising the user digital fingerprint;receiving a master digital fingerprint of a segment of a copy of the work from the server, the segment of the copy corresponding to the segment of the work, wherein the master digital fingerprint is a digital fingerprint from a high quality version of the work that comprises a feature vector of the high quality version of the work; andreplacing the user digital fingerprint with the master digital fingerprint.
  • 20. The computer readable storage medium of claim 18, the operations further comprising: performing an analysis of a quality of the segment of the work based on at least one of characteristics of the segment or characteristics of the user digital fingerprint; andquerying a server in response to determining, based on the analysis, that the quality of the segment of the work fails to satisfy a quality threshold.
RELATED APPLICATIONS

This application is a continuation of U.S. patent application Ser. No. 14/733,578, filed on Jun. 8, 2015, which is a continuation of U.S. patent application Ser. No. 13/626,709, filed on Sep. 25, 2012, both of which are herein incorporated by reference.

US Referenced Citations (333)
Number Name Date Kind
2539767 Anderson Jan 1951 A
3919479 Moon et al. Nov 1975 A
4230990 Lert, Jr. et al. Oct 1980 A
4449249 Price May 1984 A
4450531 Kenyon et al. May 1984 A
4454594 Heffron et al. Jun 1984 A
4623837 Efron et al. Nov 1986 A
4677455 Okajima Jun 1987 A
4677466 Lert, Jr. et al. Jun 1987 A
4739398 Thomas et al. Apr 1988 A
4843562 Kenyon et al. Jun 1989 A
4918730 Schulze Apr 1990 A
5210820 Kenyon May 1993 A
5247688 Ishigami Sep 1993 A
5283819 Glick et al. Feb 1994 A
5327521 Savic et al. Jul 1994 A
5437050 Lamb et al. Jul 1995 A
5442645 Ugon et al. Aug 1995 A
5504518 Ellis et al. Apr 1996 A
5581658 O'Hagan et al. Dec 1996 A
5588119 Vincent et al. Dec 1996 A
5612729 Ellis et al. Mar 1997 A
5612974 Astrachan Mar 1997 A
5613004 Cooperman et al. Mar 1997 A
5638443 Stefik et al. Jun 1997 A
5692213 Goldberg et al. Nov 1997 A
5701452 Siefert Dec 1997 A
5710916 Barbara et al. Jan 1998 A
5724605 Wissner Mar 1998 A
5732193 Aberson Mar 1998 A
5758257 Herz et al. May 1998 A
5790691 Narayanswamy et al. Aug 1998 A
5850388 Anderson et al. Dec 1998 A
5862260 Rhoads Jan 1999 A
5881182 Fiete et al. Mar 1999 A
5918223 Blum et al. Jun 1999 A
5924071 Morgan et al. Jul 1999 A
5930369 Cox et al. Jul 1999 A
5930749 Maes Jul 1999 A
5943422 Van Wie et al. Aug 1999 A
5949885 Leighton Sep 1999 A
5959659 Dokic Sep 1999 A
5983176 Hoffert et al. Nov 1999 A
6006183 Lai et al. Dec 1999 A
6006256 Zdepski et al. Dec 1999 A
6011758 Dockes et al. Jan 2000 A
6012051 Sammon, Jr. et al. Jan 2000 A
6026411 Delp Feb 2000 A
6026439 Chowdhury et al. Feb 2000 A
6044402 Jacobson et al. Mar 2000 A
6067369 Kamei May 2000 A
6067517 Bahl et al. May 2000 A
6088455 Logan et al. Jul 2000 A
6092040 Voran Jul 2000 A
6096961 Bruti et al. Aug 2000 A
6118450 Proehl et al. Sep 2000 A
6192340 Abecassis Feb 2001 B1
6195693 Berry et al. Feb 2001 B1
6229922 Sasakawa et al. May 2001 B1
6243615 Neway et al. Jun 2001 B1
6243725 Hempleman et al. Jun 2001 B1
6253193 Ginter et al. Jun 2001 B1
6253337 Maloney et al. Jun 2001 B1
6279010 Anderson Aug 2001 B1
6279124 Brouwer et al. Aug 2001 B1
6285596 Miura et al. Sep 2001 B1
6330593 Roberts et al. Dec 2001 B1
6345256 Milsted et al. Feb 2002 B1
6345274 Zhu et al. Feb 2002 B1
6360265 Falck et al. Mar 2002 B1
6363381 Lee et al. Mar 2002 B1
6366699 Kuwano et al. Apr 2002 B1
6370513 Kolawa et al. Apr 2002 B1
6374260 Hoffert et al. Apr 2002 B1
6385596 Wiser et al. May 2002 B1
6418421 Hurtado et al. Jul 2002 B1
6422061 Sunshine et al. Jul 2002 B1
6425081 Iwamura Jul 2002 B1
6434520 Kanevsky et al. Aug 2002 B1
6438556 Malik et al. Aug 2002 B1
6449226 Kumagai Sep 2002 B1
6452874 Otsuka et al. Sep 2002 B1
6453252 Laroche Sep 2002 B1
6460050 Pace et al. Oct 2002 B1
6463508 Wolf et al. Oct 2002 B1
6477704 Cremia Nov 2002 B1
6484182 Dunphy et al. Nov 2002 B1
6487641 Cusson et al. Nov 2002 B1
6490279 Chen et al. Dec 2002 B1
6496802 van Zoest et al. Dec 2002 B1
6526411 Ward Feb 2003 B1
6542869 Foote Apr 2003 B1
6550001 Corwin et al. Apr 2003 B1
6550011 Sims, III Apr 2003 B1
6552254 Hasegawa et al. Apr 2003 B2
6570991 Scheirer et al. May 2003 B1
6591245 Klug Jul 2003 B1
6609093 Gopinath et al. Aug 2003 B1
6609105 Van Zoest et al. Aug 2003 B2
6628737 Timus Sep 2003 B1
6636965 Beyda et al. Oct 2003 B1
6654757 Stern Nov 2003 B1
6675174 Bolle et al. Jan 2004 B1
6684199 Stebbings Jan 2004 B1
6690835 Brookmeyer et al. Feb 2004 B1
6714921 Stefik et al. Mar 2004 B2
6732180 Hale et al. May 2004 B1
6735699 Sasaki et al. May 2004 B1
6763069 Divakaran et al. Jul 2004 B1
6771316 Iggulden Aug 2004 B1
6771885 Agnihotri et al. Aug 2004 B1
6788800 Carr et al. Sep 2004 B1
6834308 Ikezoye et al. Dec 2004 B1
6868440 Gupta et al. Mar 2005 B1
6947909 Hoke, Jr. Sep 2005 B1
6961858 Fransdonk Nov 2005 B2
6968337 Wold Nov 2005 B2
6990453 Wang et al. Jan 2006 B2
7020635 Hamilton et al. Mar 2006 B2
7043536 Philyaw et al. May 2006 B1
7046914 Jasinschi et al. May 2006 B2
7047241 Erickson May 2006 B1
7058223 Cox Jun 2006 B2
7080049 Truitt et al. Jul 2006 B2
7090128 Farley et al. Aug 2006 B2
7107462 Fransdonk Sep 2006 B2
7150045 Koelle et al. Dec 2006 B2
7181398 Thong et al. Feb 2007 B2
7194752 Kenyon et al. Mar 2007 B1
7228293 DeTreville Jun 2007 B2
7263205 Lev Aug 2007 B2
7266645 Garg et al. Sep 2007 B2
7269556 Kiss et al. Sep 2007 B2
7281272 Rubin et al. Oct 2007 B1
7289643 Brunk et al. Oct 2007 B2
7334720 Hulst et al. Feb 2008 B2
7349552 Levy et al. Mar 2008 B2
7363278 Schmelzer et al. Apr 2008 B2
7424747 DeTreville Sep 2008 B2
7426750 Cooper et al. Sep 2008 B2
7443797 Cheung et al. Oct 2008 B2
7474759 Sternberg et al. Jan 2009 B2
7500007 Ikezoye et al. Mar 2009 B2
7529659 Wold May 2009 B2
7546120 Ulvenes Jun 2009 B1
7562012 Wold et al. Jul 2009 B1
7565327 Schmelzer Jul 2009 B2
7587502 Crawford et al. Sep 2009 B2
7593576 Meyer et al. Sep 2009 B2
7613686 Rui Nov 2009 B2
7630562 Gong et al. Dec 2009 B2
7653210 Rhoads Jan 2010 B2
7701941 O'Callaghan et al. Apr 2010 B2
7707088 Schmelzer Apr 2010 B2
7711586 Aggarwal et al. May 2010 B2
7711652 Schmelzer May 2010 B2
7770013 Rhoads et al. Aug 2010 B2
7797249 Schmelzer et al. Sep 2010 B2
7853664 Wang et al. Dec 2010 B1
7877438 Schrempp et al. Jan 2011 B2
7917645 Ikezoye et al. Mar 2011 B2
7942317 Racz et al. May 2011 B2
8006314 Wold Aug 2011 B2
8033458 Hulst et al. Oct 2011 B2
8061598 Racz et al. Nov 2011 B2
8082150 Wold Dec 2011 B2
8086445 Wold et al. Dec 2011 B2
8112818 Wold Feb 2012 B2
8122339 Bastos dos Santos et al. Feb 2012 B2
8130746 Schrempp Mar 2012 B2
8199651 Schrempp et al. Jun 2012 B1
8316238 Mergen et al. Nov 2012 B2
8332326 Schrempp et al. Dec 2012 B2
8458156 Sharifi et al. Jun 2013 B1
8472669 Sharma Jun 2013 B2
8484691 Schmelzer Jul 2013 B2
8639178 Anniballi et al. Jan 2014 B2
8645279 Schmelzer Feb 2014 B2
8732858 Wold May 2014 B2
8775317 Schmelzer Jul 2014 B2
8843952 Pora et al. Sep 2014 B2
8862795 Castro Scorsi Oct 2014 B2
8886635 Cho et al. Nov 2014 B2
8972481 Schrempp et al. Mar 2015 B2
9374183 Anniballi et al. Jun 2016 B2
9411050 Weber Aug 2016 B1
9461759 Anniballi et al. Oct 2016 B2
20010013061 DeMartin et al. Aug 2001 A1
20010027493 Wallace Oct 2001 A1
20010027522 Saito Oct 2001 A1
20010034219 Hewitt et al. Oct 2001 A1
20010037304 Paiz Nov 2001 A1
20010041989 Vilcauskas, Jr. et al. Nov 2001 A1
20010051996 Cooper et al. Dec 2001 A1
20010056430 Yankowski Dec 2001 A1
20020002899 Gjerdingen et al. Jan 2002 A1
20020019858 Kaiser et al. Feb 2002 A1
20020023020 Kenyon et al. Feb 2002 A1
20020023220 Kaplan Feb 2002 A1
20020037083 Weare et al. Mar 2002 A1
20020042754 Del Beccaro et al. Apr 2002 A1
20020049760 Scott et al. Apr 2002 A1
20020064149 Elliott et al. May 2002 A1
20020069098 Schmidt Jun 2002 A1
20020072325 Hayter et al. Jun 2002 A1
20020073316 Collins et al. Jun 2002 A1
20020076051 Nil Jun 2002 A1
20020082999 Lee et al. Jun 2002 A1
20020083060 Wang et al. Jun 2002 A1
20020087885 Peled et al. Jul 2002 A1
20020120577 Hans et al. Aug 2002 A1
20020123990 Abe et al. Sep 2002 A1
20020129140 Peled et al. Sep 2002 A1
20020133494 Goedken Sep 2002 A1
20020133499 Ward et al. Sep 2002 A1
20020141384 Liu et al. Oct 2002 A1
20020152261 Arkin et al. Oct 2002 A1
20020152262 Arkin et al. Oct 2002 A1
20020156737 Kahn et al. Oct 2002 A1
20020157005 Brunk et al. Oct 2002 A1
20020158737 Yokoyama Oct 2002 A1
20020178410 Haitsma et al. Nov 2002 A1
20020184517 Tadayon et al. Dec 2002 A1
20020186887 Rhoads Dec 2002 A1
20020198789 Waldman Dec 2002 A1
20030014530 Bodin et al. Jan 2003 A1
20030018709 Schrempp et al. Jan 2003 A1
20030023852 Wold Jan 2003 A1
20030033321 Schrempp et al. Feb 2003 A1
20030037010 Schmelzer Feb 2003 A1
20030051100 Patel Mar 2003 A1
20030061352 Bohrer et al. Mar 2003 A1
20030061490 Abajian Mar 2003 A1
20030095660 Lee et al. May 2003 A1
20030105739 Essafi et al. Jun 2003 A1
20030135623 Schrempp et al. Jul 2003 A1
20030191719 Ginter et al. Oct 2003 A1
20030191764 Richards Oct 2003 A1
20030195852 Campbell et al. Oct 2003 A1
20030223554 Zhang Dec 2003 A1
20040008864 Watson et al. Jan 2004 A1
20040010495 Kramer et al. Jan 2004 A1
20040028281 Cheng et al. Feb 2004 A1
20040053654 Kokumai et al. Mar 2004 A1
20040073513 Stefik et al. Apr 2004 A1
20040073531 Patterson Apr 2004 A1
20040089142 Georges et al. May 2004 A1
20040133797 Arnold Jul 2004 A1
20040148191 Hoke, Jr. Jul 2004 A1
20040163106 Schrempp et al. Aug 2004 A1
20040167858 Erickson Aug 2004 A1
20040199387 Wang et al. Oct 2004 A1
20040201784 Dagtas et al. Oct 2004 A9
20050021783 Ishii Jan 2005 A1
20050038819 Hicken et al. Feb 2005 A1
20050039000 Erickson Feb 2005 A1
20050044189 Ikezoye et al. Feb 2005 A1
20050097059 Shuster May 2005 A1
20050141707 Haitsma et al. Jun 2005 A1
20050154678 Schmelzer Jul 2005 A1
20050154680 Schmelzer Jul 2005 A1
20050154681 Schmelzer Jul 2005 A1
20050216433 Bland et al. Sep 2005 A1
20050267945 Cohen et al. Dec 2005 A1
20050289065 Weare Dec 2005 A1
20060034177 Schrempp Feb 2006 A1
20060062426 Levy et al. Mar 2006 A1
20060118619 Hulst et al. Jun 2006 A1
20070033409 Brunk et al. Feb 2007 A1
20070074147 Wold Mar 2007 A1
20070078769 Way Apr 2007 A1
20070124756 Covell et al. May 2007 A1
20070186229 Conklin et al. Aug 2007 A1
20070226365 Hildreth et al. Sep 2007 A1
20070271248 Albernoz et al. Nov 2007 A1
20080008173 Kanevsky et al. Jan 2008 A1
20080019371 Anschutz et al. Jan 2008 A1
20080133415 Ginter et al. Jun 2008 A1
20080141379 Schmelzer Jun 2008 A1
20080154730 Schmelzer et al. Jun 2008 A1
20080155116 Schmelzer Jun 2008 A1
20080250080 Arrasvuori Oct 2008 A1
20080263579 Mears et al. Oct 2008 A1
20080320545 Schwartz Dec 2008 A1
20090019468 Ganesan et al. Jan 2009 A1
20090030651 Wold Jan 2009 A1
20090031326 Wold Jan 2009 A1
20090043870 Ikezoye et al. Feb 2009 A1
20090063974 Bull et al. Mar 2009 A1
20090077673 Schmelzer Mar 2009 A1
20090089586 Brunk et al. Apr 2009 A1
20090131152 Busse May 2009 A1
20090132391 Jacobs May 2009 A1
20090192640 Wold Jul 2009 A1
20090216743 Coffman Aug 2009 A1
20090240361 Wold et al. Sep 2009 A1
20090306966 Hejna, Jr. Dec 2009 A1
20090328236 Schmelzer Dec 2009 A1
20100042843 Brunk et al. Feb 2010 A1
20100061560 Cronin Mar 2010 A1
20100104259 Shakya et al. Apr 2010 A1
20100281042 Windes et al. Nov 2010 A1
20100290667 Lienhart et al. Nov 2010 A1
20100290867 Nice et al. Nov 2010 A1
20110066489 Gharaat et al. Mar 2011 A1
20110069230 Polumbus et al. Mar 2011 A1
20110078719 Kenyon et al. Mar 2011 A1
20110114723 Hulst et al. May 2011 A1
20110119149 Ikezoye et al. May 2011 A1
20120124679 Wold May 2012 A1
20120223135 Meek et al. Sep 2012 A1
20120318071 Biehl et al. Dec 2012 A1
20130011008 Ikezoye et al. Jan 2013 A1
20130159021 Felsher Jun 2013 A1
20130318071 Cho et al. Nov 2013 A1
20130318114 Emerson Nov 2013 A1
20140056433 Emerson Feb 2014 A1
20140089307 Garside et al. Mar 2014 A1
20140115716 Schmelzer Apr 2014 A1
20140215643 Wold Jul 2014 A1
20140335834 Emerson Nov 2014 A1
20140336798 Emerson Nov 2014 A1
20140336799 Emerson Nov 2014 A1
20140357234 Sullivan Dec 2014 A1
20150078575 Selig et al. Mar 2015 A1
20150154273 Schrempp et al. Jun 2015 A1
20150234814 Ikezoye et al. Aug 2015 A1
20150270976 Garside et al. Sep 2015 A1
20160132664 Wold May 2016 A1
20160203824 Park et al. Jul 2016 A1
20170169235 Schmelzer Jun 2017 A1
20170366847 Covell et al. Dec 2017 A1
20180032705 Wold Feb 2018 A1
Foreign Referenced Citations (34)
Number Date Country
0349106 Jan 1990 EP
0402210 Jun 1990 EP
0459046 Apr 1991 EP
0517405 May 1992 EP
0689316 Dec 1995 EP
0731446 Sep 1996 EP
0859503 Aug 1998 EP
1354276 Dec 2007 EP
1771791 Feb 2012 EP
2464049 Dec 2012 GB
WO 9636163 Nov 1996 WO
WO 9820672 May 1998 WO
WO 00005650 Feb 2000 WO
WO 00039954 Jul 2000 WO
WO 00063800 Oct 2000 WO
WO 01023981 Apr 2001 WO
WO 01047179 Jun 2001 WO
WO 01052540 Jul 2001 WO
WO 01062004 Aug 2001 WO
WO 02003203 Jan 2002 WO
WO 02015035 Feb 2002 WO
WO 02027600 Apr 2002 WO
WO 02037316 May 2002 WO
WO 02082271 Oct 2002 WO
WO 02086803 Oct 2002 WO
WO 03009149 Jan 2003 WO
WO 03036496 May 2003 WO
WO 03067459 Aug 2003 WO
WO 03091990 Nov 2003 WO
WO 04044820 May 2004 WO
WO 03007235 Jul 2004 WO
WO 04070558 Aug 2004 WO
WO 06015168 Feb 2006 WO
WO 09017710 Feb 2009 WO
Non-Patent Literature Citations (42)
Entry
Albert, Douglas, et al., “Combatting Software Piracy by encryption and key management,” IEEE Computer Society, vol. 17. No. 4, Apr. 1984, 6 pages.
Audible Magic Corporation, “Audio Identification Technology Provides the Cornerstone for Online Distribution,” copyright 2000, downloaded from http://www.audiblemagic.com/documents/Technology_Summary.pdf.
Baum, L., et al., “A Maximization Technique Occurring in the Statistical Analysis of Probabilistic Functions of Markov Chains,” The Annals of Mathematical Statistics, vol. 41, No. 1, pp. 164-171, Feb. 1, 1970.
Beritelli, F., et al., “Multilayer chaotic encryption for secure communications in packet switching networks,” Proceedings of 2000 International Conference on Communication Technology, vol. 2, Aug. 2000, pp. 1575-1582, IEEE.
Blum, T., et al., “Audio Databases with Content-Based Retrieval,” Intelligent Multimedia Information Retrieval, May 30, 1997, pp. 113-135, MIT Press.
Breslin, Pat, et al., Relatable Website, “Emusic uses Relatable's open source audio recognition solution, TRM, to signature its music catabblog for MusicBrainz database,” Relatable Press Release, Oct. 17, 2000, http://www.relatable.com/news/pressrelease/001017.release.html, Oct. 17, 2000.
Business Wire, “Cisco and Fox Host Groundbreaking Screening of Titan A.E.; Animated Epic Will Be First Film Ever to be Digitaly Transmitted Over the Internet Monday,” Jun. 5, 2000, 08:14 EDT.
Business Wire, “IBM: IBM Announces New Descrambler Software; First to Offer Software to Work With Digital Video Chips,” Jun. 5, 25, 1997, 07:49.
Chen, et al., Yong-Cong, “A Secure and Robust Digital Watermaking Technique by the Blcok Cipher RC6 and Secure Hash Algorithm”, Proceedings of 2001 International Conference on Image Processing, Oct. 7, 2001, vol. 2, pp. 518-521, IEEE.
Cosi, P., De Poli, G., Prandoni, P., “Timbre Characterization with Mel-Cepstrum and Neural Nets,” Proceedings of the 1994 International Computer Music Conference, pp. 42-45, San Francisco, 1994.
Dempster, A.P., et al., “Maximum Likelihood from Incomplete Data via the EM Algorithm” Journal of the Royal Statistical Society, Series B (Methodological), vol. 39, Issue 1, pp. 31-38, read before the Royal Statistical Society, Dec. 8, 1976.
Feiten, B. and Gunzel, S., “Automatic Indexing of a Sound Database Using Self-Organizing Neural Nets,” Computer Music Journal, 18:3, pp. 53-65, Oct. 1, 1994, MIT.
Fischer, S. et al, “Automatic Recognition of Film Genres,” Technical reports 95 (Practical Computer Science IV), Jun. 1995, 12 pages.
Foote, J., “A Similarity Measure for Automatic Audio Classification,” Proceedings AAAI 1997 Spring Symposium on Intelligent Integration and Use of Text, Image, Video, and Audio Corpora, Mar. 1997, 7 pages.
Gasaway, Laura, “Close of Century Sees New Copyright Amendments” Mar. 2000, Information Outlook, 4, 3, 42, Brief Article, 3 pages.
Gonzalez, R. et al. “Content Based Retrieval of Audio,” ATNAC '96 Proceedings, 1996, 6 pages.
Haitsma, J., et al., “Robust Audio Hashing for Content Identification”, CBMI 2001, Second International Workshop on Content Based Multimedia and Indexing, Sep. 19-21, 2001, 8 pages, Brescia, Italy.
Harris, Lesley Ellen, “To register or not,” Mar. 2006, Information Outlook, 10, 3, 32(s).
Kanth, K.V. et al. “Dimensionality Reduction or Similarity Searching in Databases,” Computer Vision and Image understanding, vol. 75, Nos. 1/2 Jul./Aug. 1999, pp. 59-72, Academic Press. Santa Barbara, CA, USA.
Keislar, D., et al., “Audio Analysis for Content-Based Retrieval,” Proceedings of the 1995 International Computer Music Conference, copyright 1995, pp. 199-202.
Lin, et al., “Generating Robust Digital Signature for Image/Video Authentication,” Proc. Multimedia and Security workshop at ACM Multimedia'98, Sep. 1, 1998, pp. 49-54.
Ohtsuki, K., et al. , “Topic Extraction Based on Continuous Speech Recognition in Broadcast-News Speech,” Proceedings IEEE Workshop on Automated Speech Recognition and Understanding, Dec. 14, 1997, pp. 527-534, IEEE.
Packethound Tech Specs, copyright 2002, Palisade Systems, Inc., 2 pages, downloaded from www.palisdesys.com/products/packethount/tck specs/prod Phtechspecs.shtml on Apr. 16, 2002.
“How Does PacketHound Work?” and “PacketHound Protocol Management Appliance”, copyright 2002, Palisade Systems, Inc., 5 pages, downloaded from www.palisdesys.com/products/packethound/how_does_it_work/prod_Pghhow.shtml on Apr. 16, 2002.
Pankanti, Sharath, “Verification Watermarks on Fingerprint Recognition and Retrieval,” Part of IS&T/SPIE Conference on Security and Watermarking of Multimedia Contents, San Jose, CA Jan. 1999, SPIE vol. 3657, pp. 66-78.
Pellom, B. et al., “Fast Likelihood Computation Techniques in Nearest-Neighbor search for Continuous Speech Recognition.”, IEEE Signal Processing Letters, vol. 8, pp. 221-224 Aug. 2001.
Reynolds, D., et al. , “Robust Text-Independent Speaker Identification Using Gaussian Mixture Speaker Models”, IEEE Transactions on Speech and Audio Processing, vol. 3, No. 1, pp. 72-83 Jan. 1995.
Scheirer, E. D. et al., “Construction and Evaluation of a Robust Multifeature Speech/Music Discriminator,” Proceedings of International Conference on Acoustics, Speech, and Signal Processing '97, Apr. 21, 1997, vol. 2, pp. 1331-1334, IEEE.
Scheirer, E. D., “Tempo and Beat Analysis of Acoustic Musical Signals,” The Journal of the Acoustical Society of America, Jan. 1998, pp. 588-601, vol. 103 (1).
Schneier, Bruce, “Applied Cryptography, Protocols, Algorithms and Source Code in C” (2nd edition), Chapter 2: Protocol Building Blocks, copyright 1996, pp. 30-31, USA.
Smith, Alan J., “Cache Memories,” Computing Surveys, Sep. 1982, pp. 473-530, vol. 14, No. 3.
Vertegaal, R. et al., “ISEE: An Intuitive Sound Editing Environment,” Computer Music Journal, 18:2, pp. 21-29, Summer 1994.
Wang, Yao, et al., “Multimedia Content Analysis,” IEEE Signal Processing Magazine, Nov. 2000, pp. 12-36.
Wold, Erling, et al., “Content Based Classification, Search, and Retrieval of Audio,” IEEE Multimedia, 1996, pp. 27-36, vol. 3, No. 3.
Zawodny, Jeremy, D., “A C Program to Compute CDDB discids on Linus and FreeBSD,” [internet] http://jeremy.zawodny.com/c/discid-linux-1.3tar.gz, 1 page, Apr. 14, 2001, retrieved Jul. 17, 2007.
Kashino et al., “Robust Search Methods for Music Signals Based on Simple Representation”, 2007 IEEE International Conference on Acoustics, Speech and Signal Processing, Apr. 15-20, 2007, pp. 1421-1424, ICASSP 2007, IEEE, Honolulu, HI, USA, Piscataway, NJ, USA.
Haitsma et al., “A Highly Robust Audio Fingerprinting System With an Efficient Search Strategy”, Journal of New Music Research, Jun. 2003, pp. 211-221, vol. 32(2).
Jin et al, “Applications of Digital Fingerprinting and Digital Watermarking for E-Commerce Security Mechanism”, IEEE International Conference on Audio, Language and Miage Processing, Jul. 7-9, 2008, pp. 536-540, IEEE, Piscataway, NJ, USA.
White, R., “How Computers Work,” Oct. 15, 2003, Que Publishing, 7th Ed., 23 pages.
PCT Search Report PCT/US08/09127, International Search Report dated Oct. 30, 2008, 8 Pages.
International Search Report & Written Opinion dated Apr. 15, 2014, for PCT/US2013/061750.
European Patent Application No. 13840744.0 Extended European Search Report dated Sep. 5, 2016, 9 pages.
Related Publications (1)
Number Date Country
20170193104 A1 Jul 2017 US
Continuations (2)
Number Date Country
Parent 14733578 Jun 2015 US
Child 15464196 US
Parent 13626709 Sep 2012 US
Child 14733578 US