The traditional television (TV) viewing experience and the process of accessing video media over the Internet have been converging for some time and are now becoming co-dependent. As a business model, both of these forms of media delivery have experimented over the years with monthly subscription fees and pay-per-view revenue models, but the advertising-supported model remains the dominant economic engine for both.
Financial support from advertisers is usually based on the number of viewers exposed to the advertisement with the advertiser being charged a fee for every thousand “impressions” or times that the advertisement is viewed; usually called “cost per thousand” or “CPM”. Generally speaking, higher CPM rates are charged for advertising that can provide additional details about those individual impressions, such as the time of day it was viewed or the market area where the viewing occurred. Associating the impressions with demographic information regarding those seeing the advertisement is even more valuable, particularly when that demographic is one that advertisers believe to offer better prospects for positive actions regarding the product or service being promoted.
For content accessed by personal computers or any other type of Internet-connected device, a viewer's Internet browsing activities may be readily detected and captured via various techniques. The most common technique is the use of a “cookie”, also known as an HTTP cookie, web cookie, or browser cookie. This is a small data file sent from the website being browsed to the user's browser. The browser then sends the cookie back to the server every time the website is re-loaded so that the server can be made aware of the user's previous activity on that server. This approach enables “shopping carts” to retain earlier, uncompleted purchases, and to pre-authenticate users so that they do not need to re-enter certain identification.
Cookies may also be used to build a history of previous browsing. Such information is beneficially used to enable the presentation of commercial offers that are more likely to be of interest to the user than arbitrary placements. For example, a user in Philadelphia who browses a search engine, such as Google, to look for say, “Hotels in Seattle,” would find that many websites browsed later would be displaying ads for Seattle travel, tours, entertainment, local attractions, and other custom-served offers. This is a result of certain data about the search activity being stored locally on the user's computer in the form of a data cookie.
Another common technique leverages the fact that most commercial web pages are not wholly self-contained. For a variety of technical and commercial reasons, many elements seen on the displayed web page are instead assembled “on the fly” by using content downloaded from many different servers, often geographically dispersed. Hence the screen location where a certain picture, animation or advertisement would be displayed is often actually blank when initially downloaded, but contains program instructions, most commonly in the HTML, or JavaScript languages, that makes a request or “call” to the server where the needed content resides.
These requests typically include the IP address of the requesting computer, the time the content was requested, the type of web browser that made the request, the nature of the display it has to appear on, and other specifics. In addition to acting on the request and serving the requested content, the server can store all of this information and associate it with a unique tracking token, sometimes in the form of a browser cookie, attached to the content request.
Even where the web page does not need additional content to complete the user's viewing experience, this same technique can be used to gain insight into the actions and habits of the person browsing the site, which can then be used to personalize the types of advertising served to the user. This can be accomplished by programming web pages to request a graphic element from a particular server using an invisible (non-displaying) graphic file known as a “tracking pixel.” These are (usually) tiny image files (GIFs, JPEGs, PNGs, etc.) whose Internet address is put into web pages and other HTML documents. When the particular page containing such a tracking pixel is loaded, the web browser then sends a request, typically via the Internet, to a server at the address of the embedded web graphic. The addressed server sends the requested graphic file (e.g., a tracking pixel) and logs the event of the request for the specific graphic. These tracking pixel files are sometimes known by other names such as web bugs, transparent pixels, tracking bugs, pixel tags, web beacons or clear gifs. Regardless of what these token images are called, their function is largely the same.
In many commercial applications, an advertiser or its agency or other third-party service might decide to track impressions (as discussed above, an impression constitutes one person viewing one message) with a tracking pixel. Each time the advertisement is displayed, code in the displaying web page addresses some server, locally or across the Internet, containing the tracking pixel. The server answering the request then records information that can include the user's IP Address, Hostname, Device type, Screen Size, Operating System, Web browser, and the Date that the image was viewed.
In traditional TV viewing, commercial ratings data is typically collected and analyzed in an offline fashion by media research companies such as the Nielsen Company, using specialized equipment sometimes called a “Home Unit” that the research company has arranged to get connected to TV sets in a limited number of selected households. These devices record when the TV was tuned to a particular channel, however, there is currently an unmet need for reliable techniques to measure whether a specific video segment, (either broadcast content or advertisement) was actually watched by the viewer. Meanwhile, there is still no truly reliable process for confirming if and when broadcast content that has been recorded and stored on a DVR or the like is viewed at some later time.
Further, with existing monitoring services, such as Nielsen, there is a material delay between the time a program is broadcast and the availability of reliable, broadly-sampled information about what programming was watched in which markets and by what demographics is made available to either the content providers or advertisers. It is also a matter of significant controversy how valid the projections to the whole U.S. could be when they have been extrapolated from such a small sample of potential viewers (estimated to be approximately one out of every ten thousand households).
Consequently, the ability to accurately determine in near real-time exactly what TV program or advertisement each and every TV viewer in the U.S. is watching at any moment has long been an unmet market need. One reason this has been such a challenge is because it would require being able to identify not just what channel has been tuned to, but specifically what content is being watched, since the media actually being consumed by the viewer can include not just the scheduled programming but also regionally or locally-inserted advertisements, content that has been time-shifted, or other entertainment products.
Some attempts have been made to use audio matching technology to map what is being heard on the home TV set to a database of “audio fingerprints.” This is a process that purports to match the fingerprints to certain specific content. The speed and reliability of such technology that has been made commercially available to date has been found to have limitations. Video matching of screen images to known content is computationally more challenging than using audio but theoretically more accurate and useful. Matching the video segment being viewed to a database of samples (including those extracted only seconds previously from a live TV event) has offered a substantial technical challenge but has been effectively employed and is taught in U.S. Pat. No. 8,595,781, among others.
The subject matter disclosed in detail below is directed to a real-time content identification and tracking system enabling monitoring of television programming consumption specific to an individual television or other viewing device. Metrics collected may include data regarding viewing of specific broadcast media, commercial messages, interactive on-screen information or other programming, as well as locally cached, time-shifted programming. Information about media consumption by such specific television sets or other viewing means may be returned to a commercial client of the system through a trusted third-party intermediary service and, in certain embodiments, encoded tokens may be used to manage the display of certain events as well as to enable robust auditing of each involved party's contractual performance.
More specifically, the systems and methods disclosed herein enable the identification of a video segment being watched or the identification of an interactive message being displayed on a video screen of any connected TV viewing device, such as a smart TV, a TV with a cable set-top box, or a TV with an Internet-based set-top box. Furthermore, this video segment identification system accurately identifies the segments whether broadcast, previously recorded, or a commercial message, while incorporating that ability into an integrated system enabling the provision of a number of new products and services to commercial clients in many ways similar to the usage tracking functionality provided by so-called cookies and tracking pixels for media consumption over the Internet. Various embodiments of systems and methods are described in detail below from the perspective of commercial practicality.
The ability to monitor the viewing of events on Internet-connected televisions at a multiplicity of locations can be used in conjunction with the display of contextually targeted content. The contextually targeted content is usually embedded within a contextually targeted display application module (hereinafter “contextually targeted display application”). One or more contextually targeted display applications are then sent ahead of time from the central server means to (and loaded in) each participating TV system prior to the display of a video segment of interest associated with those application modules. Sometimes when a contextually targeted display application is executed, the contextually targeted display application calls out to other servers across the Internet to get additional (or current) information to update, or add to, the content already embedded within the application module. All content of a contextually targeted display application, whether sent in advance or retrieved on execution, appears within the framework of a contextually targeted display application window which pops up on the TV screen for the user to view and sometimes interact with. It should be appreciated, however, that sometimes the contextually targeted display application's role is not to display anything but rather to simply call an embedded URL address (or send an embedded encoded token) to trigger an auditing means to register (i.e., log) a viewing event.
One aspect of the subject matter disclosed in detail below is a method, performed by a computer system, for automatically logging a viewing event on a screen of a television system, comprising the following operations: (a) storing a respective reference data set for each of a multiplicity of reference video segments in a database; (b) loading a multiplicity of contextually targeted display applications in a memory of the television system, each contextually targeted display application having a respective tracking pixel URL address embedded therein; (c) receiving video fingerprints from the television system at a server, the video fingerprints being derived from television signals for respective portions of a video segment being displayed on the screen; (d) searching the database to identify a reference data set that most matches the video fingerprint; (e) in response to identification of the matching reference data set in operation (d), identifying a contextually targeted display application which is associated with the matching reference data set; (f) in response to identification of the associated contextually targeted display application in operation (e), sending a signal identifying the associated contextually targeted display application to the television system; (g) sending a request for a tracking pixel from the television system to a server using the tracking pixel URL address embedded in the associated contextually targeted display application; (h) sending a tracking pixel from the server to the television system in response to receipt of the request for a tracking pixel; and (i) logging receipt of the request for a tracking pixel in a memory of the server. The request for the tracking pixel may include information identifying the TV system, information indicative of the geographical location of the TV system, information identifying the contextually targeted content, and the time when the request for the tracking pixel was received by the server.
Another aspect of the subject matter disclosed below is a system for automatically logging a viewing event on a screen of a television system the system comprising a television system having a screen, first and second servers, and a database which communicate via a network. The database stores a respective reference data set for each of a multiplicity of reference video segments. The television system is programmed to derive video fingerprints from television signals for a respective portion of a video segment being displayed on the screen. The first server is programmed to: load a multiplicity of contextually targeted display applications in a memory of the television system, each contextually targeted display application having a respective tracking pixel URL address embedded therein; receive the video fingerprints from the television system; search the database to identify a reference data set that most matches the video fingerprint; identify a contextually targeted display application which is associated with the matching reference data set; and send a signal identifying the associated contextually targeted display application to the television system. The TV system is further programmed to send a request for a tracking pixel to the tracking pixel URL address embedded in the associated contextually targeted display application, which tracking pixel URL address is located at the second server. The second server is programmed to receive the request for a tracking pixel from the television system, send the tracking pixel to the television system, and log receipt of the request for a tracking pixel in memory.
A further aspect is a method, performed by a computer system, for automatically logging a viewing event on a screen of a television system, comprising the following operations: (a) storing a respective reference data set for each of a multiplicity of reference video segments in a database; (b) loading a multiplicity of contextually targeted display applications in a memory of the television system, each contextually targeted display application having a respective encoded token embedded therein; (c) receiving video fingerprints from the television system at a server, the video fingerprints being derived from television signals for respective portions of a video segment being displayed on the screen; (d) searching the database to identify a reference data set that most matches the video fingerprint; (e) in response to identification of the matching reference data set in operation (d), identifying a contextually targeted display application which is associated with the matching reference data set; (f) in response to identification of the associated contextually targeted display application in operation (e), sending a signal identifying the associated contextually targeted display application to the television system; (g) sending an encoded token embedded in the associated contextually targeted display application from the television system to an auditing server; (h) decoding the encoded token at the auditing server; and (i) logging receipt of the encoded token in a memory of the auditing server.
Yet another aspect is a system for automatically logging a viewing event on a screen of a television system the system comprising a television system having a screen, first and second servers, and a database which communicate via a network. The database stores a respective reference data set for each of a multiplicity of reference video segments. The television system is programmed to derive video fingerprints from television signals for a respective portion of a video segment being displayed on the screen. The first server is programmed to: load a multiplicity of contextually targeted display applications in a memory of the television system, each contextually targeted display application having a respective encoded token embedded therein; receive video fingerprints from the television system, the video fingerprints being derived from television signals for respective portions of a video segment being displayed on the screen; search the database to identify a reference data set that most matches the video fingerprint; identify a contextually targeted display application which is associated with the matching reference data set; and send a signal identifying the associated contextually targeted display application to the television system. The TV system is further programmed to send an encoded token embedded in the associated contextually targeted display application to the second server. The second server is programmed to receive and decode the encoded token from the television system and log receipt of the encoded token in a memory.
Other aspects of systems and methods for automatically logging viewing events on Internet-connected televisions are disclosed below.
Reference will hereinafter be made to the drawings in which similar elements in different drawings bear the same reference numerals.
The means of using tracking pixels is a legacy from personal computers and web browsers. When a web browser addresses a web site, the web server sends a program to the web browser in the form of hyper-text markup language (HTML), which itself contains many subprogram modules such as Java, Adobe Flash and JavaScript, among others. Furthermore, these elements often come from different servers.
All of the information (text, graphics, videos) is assembled by the HTML program into a single displaying page within the computer's browser. Within the displayed page will be various windows, some with graphics, some with video. Also, on the web page will be advertisements from various sponsors. The ads themselves are made up of HTML code. This HTML code will also contain Java, Flash, JavaScript and other program elements. This code is supplied to the web site operator by the ad agency representing the advertiser.
Hundreds to thousands of lines of computer code instructs the computer web browser on exactly what text, graphics and video to display, including what fonts to use, what color of text, color of background, precisely where text and pictures are displayed or video windows are positioned. Among the program elements supplied by the ad agency will be a graphic element in JPEG or PNG format, just like what comes from a digital camera, called a ‘tracking pixel’. It might be a one-by-one pixel size and set to be 100% transparent so that it does not show in the displayed content. However, when the computer browser executes the HTML code from the web site, when the program gets to the advertisement, the browser calls out across the Internet to the advertiser's servers (one for graphics, one for video (if any), and one for event tracking (auditing)) to get the various elements to form the ad window subsection of the web page. The HTML reads a program element called a GET which instructs the program to call a URL to, among other things, obtain something needed for the rendering and display of a webpage. When executing this instruction (i.e., go get the graphic element at the URL address), it makes a call to the advertiser's server (hereinafter “ad server”) at that URL address. That ad server then sends the element (the tracking pixel, in this example) back to the web browser of the client system. The display of the tracking pixel is irrelevant but the act of the ad server responding to the GET call from the web browser of the client system causes an event to be logged that tells the advertiser that an ad was displayed on a web page in, for example, Weehawken, N.J. The ad server will also log the time and date of the request.
This means of auditing advertisements allows a high degree of confidence in the system compared to a web site operator merely reporting back to the advertiser the number of times a web page was displayed. However, the web site operator also wants to know how many times the ad was displayed so it can track its own advertisement billing. Due to the complexities of web servers and web browser, a server may send one or more pages of HTML, but not all of it gets displayed, so in the case of the example above, neither the web site operator nor the advertiser could know how often the ad had been displayed from only statistics of the web site operator's servers sending out the HTML code upon the request of a web browser in some home.
In accordance with the systems disclosed hereinafter, the foregoing tracking pixel methodology is extended to smart TVs that contain a small computer or processor programmed to execute a web browser application. This computer system inside the TV system can take over the screen of the TV and display the very same content one sees on a personal computer. However, the use of this computer system is usually toward providing a “walled garden” of pre-programmed applications very similar to a smart phone. Such pre-loaded programs (applications) might be an application to watch movies from over the Internet or an application to get the latest news. The resulting user experience is almost identical to a smart phone or iPad experience. In reality, these applications are basically just pre-packaged web scripts usually written in HTML. When the application runs, it invokes a software program call to a web server to send all the information needed to display the web page. Of course, the information received from web site operator by the smart TV is in a format suitable for a larger display 10 feet from the viewer as opposed to an iPad held in one's hands. This programmatic means by itself could not be applied to live television as this Internet language of HTML was intended as a static means of linking information from multiple computers (not to be confused with the ability of webpages to display video within windows on said web page).
The novelty of the video tracking pixel disclosed herein stems from using this underlying technology of tracking pixels, but extending its utility into video by applying video matching whereby the act of identifying a video segment by a video matching means can be used to trigger a program to run in the computer system of a smart TV or set-top box. When that program runs, part of its program code addresses a distant computer server to request that the server send a graphic element back to the program operating in the smart TV or set-top box. The system of video tracking pixels is using existing Internet programmatic language and existing Internet server means used for the prior art of webpage tracking pixels.
The uses of tracking pixels in the context of television provides a means for a third party to verify that a video segment of interest to the third party has been displayed on a television. Again, this video segment of interest could be an advertisement of a company's product or an advertisement of a competitor's product. For example, Competitor A, the Ford Motor company, might like to know how many times an ad of a Competitor B, the Toyota Motor Company, is seen in a particular market. Competitor A can obtain this information by contracting the video tracking pixel service to place an application in every smart TV in a market area of interest, e.g., New York City metropolitan area, that triggers every time a Competitor B ad is displayed on the respective TV. In other uses, if the application that is triggered in the home displays contextually targeted information (information that appears on the television screen in a pop-up window), this event is audited by the same means as the previous example of simply detecting the display of a video segment of interest. That is, the video tracking pixel provides an independent means for the customer of a contextually targeted information service to verify the delivery to and subsequent display of the service to a multiplicity of televisions.
Current means of auditing the display of television programming or advertisements are inexact because, for instance, the buyer of a TV ad spot only knows how many times that buyer's ad was broadcast but not how many TV sets were on and tuned to the channel when the ad was aired. Several companies have devised means to statistically measure household TV viewing events but this is a very inexact science and cannot accurately measure actually viewing. For instance, at a commercial break, the viewer might tune away to check another channel and miss the advertisement. By means of the video tracking pixel methodology disclosed in detail below, the actual viewing of the ad (or any video segment of interest) can be measured. If the ad involves contextually targeted information, the display of this additional information can likewise be verified.
Methods for matching viewed video with reference video stored in a database will now be described with reference to
As can be seen in
The matching server 101 preferably comprises a multiplicity of centrally located matching servers, only one of which is depicted in
Referring to
More specifically, the video fingerprints that result from the processing in the TV system 108 are passed via communication channel 107 to a video segment recognition processor 105 that is part of the matching server 101. The fingerprints of the unknown video are generated by the TV client 109 using an algorithm which is similar to the algorithm used by the matching server 101 to store the reference videos in the reference database 103. The video segment recognition processor 105 continuously searches the reference database 103, attempting to find a match of the incoming video fingerprints using a search means according to methods known in the art such as the method taught by Neumeier et al. in U.S. Pat. No. 8,595,781, the disclosure of which is incorporated by reference herein in its entirety. When video segment recognition processor 105 finds a match of a known fingerprint in reference database 103 with an unknown fingerprint of a video segment received from TV system 108, the video segment recognition processor 105 sends a message to a contextual targeting manager 104 identifying the video segment being displayed by the TV system 108. (As used herein, the term “manager” refers to a processor or computer programmed to execute application software for performing a data management or data processing function.) The contextual targeting manager 104 determines what, if any, events are to be associated with the detection of the newly identified video fingerprint from TV client 109. Upon determining the appropriate response, the contextual targeting manager 104 sends a coded trigger to an application manager 110 of the TV system 108 via communication channel 106. (The application manager 110 is software running on the same processor in TV system 108 that the TV client software is running on.) The application manager 110 launches and triggers or otherwise signals the specific application that has been determined to be associated with that event.
More specifically, the application manager 110 sends a trigger signal to a contextually targeted display application 112 via a communication channel 111. The TV system 108 may be loaded with multiple contextually targeted display applications. (The contextually targeted display application 112 is software running on the same processor in TV system 108 that the TV client software is running on.) In one example, a contextually targeted display application 112 may be invoked to display a related graphic image overlaid on the video screen of the TV system 108 with information related to, for example, a television advertisement currently being displayed. The graphic overlay comes from either an embedded graphic stored within the contextually targeted display application (previously downloaded from the contextual targeting manager 104). Or the image can come from an external website when the contextually targeted display application renders the overlay. Similar to a web browser, the contextually targeted display application can contain URLs that point to external web sites for requesting graphics and/or videos.
Following display of the overlay, the contextually targeted display application 112 sends an event complete message via communication channel 115 to the contextual targeting manager 104, which records occurrence of the action. This last step is useful when an advertiser or another third party wishes to receive confirmation of the display on a TV system 108 of the contextually targeted additional information overlay or even just that a video segment, such as an advertisement or public service announcement, has been displayed. In these cases, the contextual targeting manager 104 might provide, for example, a log file of occurrences by time and location to a third party.
The TV client 109 being monitored sends video fingerprints of what is being viewed, consisting of multiple samples per second of the unknown programming being displayed on the TV 109, to the matching server 101. These video fingerprints, which contain “clues” regarding the video segment being viewed, are sent via communication channel 107 to the video segment recognition processor 105, which attempts to match the “clues” with data in the reference database 103 to identify the programming being viewed and a specific segment of the same in the samples sent, and then passes a token pointing to that information and the associated metadata for it to the contextual targeting manager 104. If and when such a segment of interest is identified, the contextual targeting manager 104 then determines what, if any, actions are to be performed. That determination is sent via communication channel 106 to the application manager 110 of TV system 108, which routes the information (e.g., in the form of a software script) via a communication channel 111 to the contextually targeted display application 112. The contextually targeted display application 112 then sends a request for a piece of content to display via a communication channel 113 (e.g., the Internet) to an address based on a URI embedded in the software script that was provided by the application manager 110. This request addresses a client server 116 somewhere on the Internet. The location of the client server 116 is not material to the process disclosed herein (i.e., the client server 116 can be located anywhere). The client server 116 returns a data item, perhaps a small graphic (i.e., tracking pixel) with transparent pixels (e.g., a .png file), via a communication channel 114. Upon receipt of this data item, the contextually targeted display application 112 assembles the remainder of the display elements, if any, and presents an image on the screen of the TV system 108, much like a web page is made up of addressable elements to be assembled by a web browser for display on a screen of a personal computer. The request for the specific graphic element sent via communication channel 113 by the contextually targeted display application 112 provides information to the commercial client's server 116 that the TV system 108 has viewed the video segment of interest and that a contextually related graph overlay has been presented. For example, the client server 116 may log that event when it sends the tracking pixel via communication channel 114 in response to receipt of a GET call via communication channel 113. (As previously noted, the tracking pixel is not displayed on the TV system. The primary purpose for sending the tracking pixel in response to the GET call is to complete the request so that the GET call will not be repeated.)
Another task of the contextually targeted display application 112 might be to pass a confirmation (i.e., event logging) message via communication channel 115 back to the matching server 101 to be logged for perhaps billing purposes or network reliability monitoring. The disadvantage of this embodiment is that it requires that the commercial client be an active participant in the process, burdened with maintaining its own client server 116 with a database of graphic elements (also known to the art as tracking pixels) while logging specifics of the video segment matches found based on the received requests for the graphics.
Optionally, a particular contextually targeted display application 112 can be triggered to send a request for a tracking pixel, with other information including a TV system identifier, location, etc., without requesting any content to be displayed in a graphic overlay on the TV screen. Since the request for a tracking pixel was triggered by the matching server 102 identifying an associated video segment being viewed, the client server 116 could log that event (i.e., the display of the identified video segment on the identified TV system) upon receipt of the request for tracking pixel. This methodology would allow a client server to determine the number of TV systems which viewed a particular video segment within a region of interest even when contextually targeted material is not being supplied.
Still referring to
Optionally, the contextually targeted display application 312 also sends a confirmation of the event via communication channel 317b to the contextual targeting manager 304, thereby providing a single source for both billing and verification data, for example. Optionally, the confirmation auditing server 318 may also provide a message via a communication channel 317a to the contextual targeting manager 304 indicating that the client server 316 has been notified. This means might be used to maintain an internal display confirmation audit trail of the confirmation auditing server 318.
More specifically, the video segment recognition processor 405 attempts to match the received clues to the reference data in the database 403 to identify the programming and specific segment of same in the samples sent, and passes a token pointing to that information and the associated metadata for it to the contextual targeting manager 404. If and when such a segment of interest is identified, the contextual targeting manager 404 then determines what, if any, actions are to be performed. When an action is to take place on the TV system 408, that determination is sent via communication channel 406 to the application manager 410 along with a token and/or encryption seed (public key value) received from the client server 416 via a communication channel 421. The token and/or encryption seed may subsequently be used by client server 416 to uniquely identify, for verification or other purposes, any event, action, or metric associated with the token. The application manager 410 then routes that information via communication channel 411 to the contextually targeted display application 412, which then displays a related graphic image overlaid on the video screen of the TV system 408. The contextually targeted display application 412 is programmed to notify the confirmation auditing server 418 via communication channel 415a that the video segment of interest (typically identified by its time stamp and associated metadata provided by the matching server 401) has been viewed by a certain TV system 408 that has been appropriately identified by device, time, location, or other information through the associated metadata. This notification may include a request that the client server 416 send a tracking pixel, which tracking pixel is sent via communication channel 415b. The confirmation auditing server 418 in turn passes an audited event report containing a viewing detection event indicator and associated metadata via a communication channel 419 to the client server 416.
Optionally, the contextually targeted display application 412 also sends a confirmation of the event via communication channel 417b to the contextual targeting manager 404. Optionally, confirmation auditing server 418 may also provide a message via a communication channel 417a to the contextual targeting manager 404 indicating that the client server 416 has been notified. Optionally, the contextual targeting manager 404 sends an unaudited event report to the client server 416 via a communication channel 420.
It will be apparent to one skilled in the art that a token as described above can be gainfully applied to the task of identifying confirmations received by the third-party verification service 418 from the TV system 408. For example, the client server 416 could supply a unique token for each of the top 120 demographic marketing areas (DMA) of the United States. It would then be the responsibility of the matching server 401 to distribute the respective tokens to TV systems residing in the respective DMAs in advance of the anticipated use of the tokens. When the system disclosed herein detects a video segment, such as a TV advertisement, and the TV system 408 is instructed to send a message to the third-party verification service 418, a token identifying the DMA region is passed as part of the message. This assists the client server 416 in classifying the collected data. The tokens can be created for classification tasks in addition to the example of regional identification disclosed herein. Also a plurality of combinations of parameters can be assigned to tokens or multiple tokens can be distributed to the TV systems for any combination of useful metrics.
If the client has supplied an encryption seed as a token or in addition to a token, such as a public key value of a public key/private key encryption pair, the encryption seed may be algorithmically processed by the computing means of the TV system 408 to generate a unique encrypted code that, when passed to the third-party verification service 418, is further passed back to the client server 416 for positive identification of specific TV systems and any video segments viewed upon those specific TV systems.
While systems and methods have been described with reference to various embodiments, it will be understood by those skilled in the art that various changes may be made and equivalents may be substituted for elements thereof without departing from the scope of the teachings herein. In addition, many modifications may be made to adapt the concepts and reductions to practice disclosed herein to a particular situation. Accordingly, it is intended that the subject matter covered by the claims not be limited to the disclosed embodiments.
As used in the claims, the term “computer system” should be construed broadly to encompass a system having at least one computer or processor, and which may have multiple computers or processors that communicate through a network or bus. As used in the preceding sentence, the terms “computer” and “processor” both refer to devices comprising a processing unit (e.g., a central processing unit) and some form of memory (i.e., computer-readable medium) for storing a program which is readable by the processing unit.
The method claims set forth hereinafter should not be construed to require that the steps recited therein be performed in alphabetical order (alphabetical ordering in the claims is used solely for the purpose of referencing previously recited steps) or in the order in which they are recited. Nor should they be construed to exclude any portions of two or more steps being performed concurrently or alternatingly.
The present application is a Continuation of U.S. patent application Ser. No. 14/763,158, filed Jul. 23, 2015, entitled “MONITORING INDIVIDUAL VIEWING OF TELEVISION EVENTS USING TRACKING PIXELS AND COOKIES,” which is a National Stage Entry of PCT/US14/72255, filed Dec. 23, 2014, entitled “MONITORING INDIVIDUAL VIEWING OF TELEVISION EVENTS USING TRACKING PIXELS AND COOKIES,” which claims the benefit of U.S. Provisional Patent Application No. 61/920,086, filed Dec. 23, 2013. The present application is also a Continuation-in-Part of U.S. patent application Ser. No. 14/551,933, filed Nov. 24, 2014, entitled “METHODS FOR IDENTIFYING VIDEO SEGMENTS AND DISPLAYING CONTEXTUALLY TARGETED CONTENT ON A CONNECTED TELEVISION.” The entire contents of each of the patent applications identified above are hereby incorporated by reference in their entirety for all purposes.
Number | Name | Date | Kind |
---|---|---|---|
4677466 | Lert, Jr. et al. | Jun 1987 | A |
4697209 | Kiewit et al. | Sep 1987 | A |
4739398 | Thomas et al. | Apr 1988 | A |
5019899 | Boles et al. | May 1991 | A |
5193001 | Kerdranvrat | Mar 1993 | A |
5319453 | Copriviza et al. | Jun 1994 | A |
5436653 | Ellis et al. | Jul 1995 | A |
5481294 | Thomas et al. | Jan 1996 | A |
5557334 | Legate | Sep 1996 | A |
5572246 | Ellis et al. | Nov 1996 | A |
5812286 | Li | Sep 1998 | A |
5826165 | Echeita et al. | Oct 1998 | A |
5918223 | Blum et al. | Jun 1999 | A |
6008802 | Goldschmidt et al. | Dec 1999 | A |
6025837 | Matthews, III et al. | Feb 2000 | A |
6035177 | Moses et al. | Mar 2000 | A |
6064764 | Bhaskaran et al. | May 2000 | A |
6381362 | Deshpande et al. | Apr 2002 | B1 |
6415438 | Blackketter et al. | Jul 2002 | B1 |
6463585 | Hendricks et al. | Oct 2002 | B1 |
6469749 | Dimitrova | Oct 2002 | B1 |
6577346 | Perlman | Jun 2003 | B1 |
6577405 | Kranz et al. | Jun 2003 | B2 |
6628801 | Powell et al. | Sep 2003 | B2 |
6647548 | Lu et al. | Nov 2003 | B1 |
6675174 | Bolle et al. | Jan 2004 | B1 |
6771316 | Iggulden | Aug 2004 | B1 |
6804659 | Graham et al. | Oct 2004 | B1 |
6978470 | Swix et al. | Dec 2005 | B2 |
6990453 | Wang et al. | Jan 2006 | B2 |
7028327 | Dougherty et al. | Apr 2006 | B1 |
7039930 | Goodman et al. | May 2006 | B1 |
7050068 | Bastos et al. | May 2006 | B1 |
7051351 | Goldman et al. | May 2006 | B2 |
7064796 | Roy et al. | Jun 2006 | B2 |
7089575 | Agnihotri et al. | Aug 2006 | B2 |
7098959 | Mishima et al. | Aug 2006 | B2 |
7136875 | Anderson et al. | Nov 2006 | B2 |
7210157 | Devara | Apr 2007 | B2 |
7346512 | Wang et al. | Mar 2008 | B2 |
7356830 | Dimitrova | Apr 2008 | B1 |
7421723 | Harkness et al. | Sep 2008 | B2 |
7545984 | Kiel et al. | Jun 2009 | B1 |
7590998 | Hanley | Sep 2009 | B2 |
7623823 | Zito et al. | Nov 2009 | B2 |
7787696 | Wilhelm et al. | Aug 2010 | B2 |
7793318 | Deng | Sep 2010 | B2 |
7933451 | Kloer | Apr 2011 | B2 |
8001571 | Schwartz et al. | Aug 2011 | B1 |
8037496 | Begeja et al. | Oct 2011 | B1 |
8094872 | Yagnik et al. | Jan 2012 | B1 |
8171004 | Kaminski, Jr. et al. | May 2012 | B1 |
8171030 | Peira et al. | May 2012 | B2 |
8175413 | Ioffe et al. | May 2012 | B1 |
8189945 | Stojancic et al. | May 2012 | B2 |
8195689 | Ramanathan et al. | Jun 2012 | B2 |
8229227 | Stojancic et al. | Jul 2012 | B2 |
8335786 | Peira et al. | Dec 2012 | B2 |
8364703 | Ramanathan et al. | Jan 2013 | B2 |
8385644 | Stojancic et al. | Feb 2013 | B2 |
8392789 | Biscondi et al. | Mar 2013 | B2 |
8494234 | Djordjevic et al. | Jul 2013 | B1 |
8522283 | Laligand et al. | Aug 2013 | B2 |
8595781 | Neumeier et al. | Nov 2013 | B2 |
8619877 | McDowell | Dec 2013 | B2 |
8625902 | Baheti et al. | Jan 2014 | B2 |
8769854 | Battaglia | Jul 2014 | B1 |
8776105 | Sinha et al. | Jul 2014 | B2 |
8832723 | Sinha et al. | Sep 2014 | B2 |
8856817 | Sinha et al. | Oct 2014 | B2 |
8893167 | Sinha et al. | Nov 2014 | B2 |
8893168 | Sinha et al. | Nov 2014 | B2 |
8898714 | Neumeier et al. | Nov 2014 | B2 |
8918804 | Sinha et al. | Dec 2014 | B2 |
8918832 | Sinha et al. | Dec 2014 | B2 |
8930980 | Neumeier et al. | Jan 2015 | B2 |
8959202 | Haitsma et al. | Feb 2015 | B2 |
9055309 | Neumeier et al. | Jun 2015 | B2 |
9055335 | Neumeier et al. | Jun 2015 | B2 |
9071868 | Neumeier et al. | Jun 2015 | B2 |
9094714 | Neumeier et al. | Jul 2015 | B2 |
9094715 | Neumeier et al. | Jul 2015 | B2 |
9262671 | Unzueta | Feb 2016 | B2 |
9368021 | Touloumtzis | Jun 2016 | B2 |
9449090 | Neumeier et al. | Sep 2016 | B2 |
9465867 | Hoarty | Oct 2016 | B2 |
9838753 | Neumeier et al. | Dec 2017 | B2 |
9955192 | Neumeier et al. | Apr 2018 | B2 |
20010039658 | Walton | Nov 2001 | A1 |
20010044992 | Jahrling | Nov 2001 | A1 |
20020026635 | Wheeler et al. | Feb 2002 | A1 |
20020054069 | Britt et al. | May 2002 | A1 |
20020054695 | Bjorn et al. | May 2002 | A1 |
20020056088 | Silva, Jr. et al. | May 2002 | A1 |
20020059633 | Harkness et al. | May 2002 | A1 |
20020083060 | Wang et al. | Jun 2002 | A1 |
20020100041 | Rosenberg et al. | Jul 2002 | A1 |
20020105907 | Bruekers et al. | Aug 2002 | A1 |
20020120925 | Logan | Aug 2002 | A1 |
20020122042 | Bates | Sep 2002 | A1 |
20020162117 | Pearson et al. | Oct 2002 | A1 |
20020162118 | Levy et al. | Oct 2002 | A1 |
20030026422 | Gerheim et al. | Feb 2003 | A1 |
20030086341 | Wells | May 2003 | A1 |
20030105794 | Jasinschi | Jun 2003 | A1 |
20030121037 | Swix et al. | Jun 2003 | A1 |
20030121046 | Roy et al. | Jun 2003 | A1 |
20030147561 | Faibish et al. | Aug 2003 | A1 |
20030188321 | Shoff et al. | Oct 2003 | A1 |
20040045020 | Witt et al. | Mar 2004 | A1 |
20040059708 | Dean et al. | Mar 2004 | A1 |
20040183825 | Stauder et al. | Sep 2004 | A1 |
20040216171 | Barone et al. | Oct 2004 | A1 |
20040221237 | Foote et al. | Nov 2004 | A1 |
20040226035 | Hauser | Nov 2004 | A1 |
20040240562 | Bargeron et al. | Dec 2004 | A1 |
20050015795 | Iggulden | Jan 2005 | A1 |
20050015796 | Bruckner et al. | Jan 2005 | A1 |
20050027766 | Ben | Feb 2005 | A1 |
20050066352 | Herley | Mar 2005 | A1 |
20050120372 | Itakura | Jun 2005 | A1 |
20050172312 | Lienhart et al. | Aug 2005 | A1 |
20050207416 | Rajkotia | Sep 2005 | A1 |
20050209065 | Schlosser et al. | Sep 2005 | A1 |
20050235318 | Grauch et al. | Oct 2005 | A1 |
20060029286 | Lim et al. | Feb 2006 | A1 |
20060029368 | Harville | Feb 2006 | A1 |
20060031914 | Dakss et al. | Feb 2006 | A1 |
20060133647 | Werner et al. | Jun 2006 | A1 |
20060153296 | Deng | Jul 2006 | A1 |
20060155952 | Haas | Jul 2006 | A1 |
20060173831 | Basso et al. | Aug 2006 | A1 |
20060187358 | Lienhart et al. | Aug 2006 | A1 |
20060193506 | Dorphan et al. | Aug 2006 | A1 |
20060195857 | Wheeler et al. | Aug 2006 | A1 |
20060195860 | Eldering et al. | Aug 2006 | A1 |
20060245724 | Hwang et al. | Nov 2006 | A1 |
20060245725 | Lim | Nov 2006 | A1 |
20060253330 | Maggio et al. | Nov 2006 | A1 |
20060294561 | Grannan et al. | Dec 2006 | A1 |
20070033608 | Eigeldinger | Feb 2007 | A1 |
20070050832 | Wright et al. | Mar 2007 | A1 |
20070061724 | Slothouber et al. | Mar 2007 | A1 |
20070061831 | Savoor et al. | Mar 2007 | A1 |
20070083901 | Bond | Apr 2007 | A1 |
20070094696 | Sakai | Apr 2007 | A1 |
20070109449 | Cheung | May 2007 | A1 |
20070113263 | Chatani | May 2007 | A1 |
20070139563 | Zhong | Jun 2007 | A1 |
20070143796 | Malik | Jun 2007 | A1 |
20070168409 | Cheung | Jul 2007 | A1 |
20070180459 | Smithpeters et al. | Aug 2007 | A1 |
20070192782 | Ramaswamy | Aug 2007 | A1 |
20070250901 | McIntire et al. | Oct 2007 | A1 |
20070261070 | Brown et al. | Nov 2007 | A1 |
20070261075 | Glasberg | Nov 2007 | A1 |
20070271300 | Ramaswamy | Nov 2007 | A1 |
20070274537 | Srinivasan | Nov 2007 | A1 |
20070300280 | Turner et al. | Dec 2007 | A1 |
20080044102 | Ekin | Feb 2008 | A1 |
20080046945 | Hanley | Feb 2008 | A1 |
20080089551 | Heather et al. | Apr 2008 | A1 |
20080138030 | Bryan et al. | Jun 2008 | A1 |
20080155588 | Roberts et al. | Jun 2008 | A1 |
20080155627 | O'Connor et al. | Jun 2008 | A1 |
20080172690 | Kanojia et al. | Jul 2008 | A1 |
20080208891 | Wang et al. | Aug 2008 | A1 |
20080240562 | Fukuda et al. | Oct 2008 | A1 |
20080263620 | Berkvens et al. | Oct 2008 | A1 |
20080276266 | Huchital et al. | Nov 2008 | A1 |
20080310731 | Stojancic et al. | Dec 2008 | A1 |
20080313140 | Pereira et al. | Dec 2008 | A1 |
20090007195 | Beyabani | Jan 2009 | A1 |
20090024923 | Hartwig et al. | Jan 2009 | A1 |
20090028517 | Shen et al. | Jan 2009 | A1 |
20090052784 | Covell et al. | Feb 2009 | A1 |
20090087027 | Eaton et al. | Apr 2009 | A1 |
20090088878 | Otsuka et al. | Apr 2009 | A1 |
20090100361 | Abello et al. | Apr 2009 | A1 |
20090131861 | Braig et al. | May 2009 | A1 |
20090172728 | Shkedi et al. | Jul 2009 | A1 |
20090172746 | Aldrey et al. | Jul 2009 | A1 |
20090175538 | Bronstein et al. | Jul 2009 | A1 |
20090213270 | Ismert et al. | Aug 2009 | A1 |
20090235312 | Morad et al. | Sep 2009 | A1 |
20100010648 | Bull et al. | Jan 2010 | A1 |
20100083299 | Nelson | Apr 2010 | A1 |
20100115543 | Falcon | May 2010 | A1 |
20100125870 | Ukawa et al. | May 2010 | A1 |
20100166257 | Wredenhagen | Jul 2010 | A1 |
20100199295 | Katpelly et al. | Aug 2010 | A1 |
20100235486 | White et al. | Sep 2010 | A1 |
20100253838 | Garg et al. | Oct 2010 | A1 |
20100269138 | Krikorian et al. | Oct 2010 | A1 |
20100306805 | Neumeier et al. | Dec 2010 | A1 |
20100306808 | Neumeier et al. | Dec 2010 | A1 |
20110015996 | Kassoway et al. | Jan 2011 | A1 |
20110026761 | Radhakrishnan et al. | Feb 2011 | A1 |
20110041154 | Olson | Feb 2011 | A1 |
20110055552 | Francis et al. | Mar 2011 | A1 |
20110096955 | Voloshynovskiy et al. | Apr 2011 | A1 |
20110251987 | Buchheit | Apr 2011 | A1 |
20110247042 | Mallinson | Oct 2011 | A1 |
20110289099 | Quan | Nov 2011 | A1 |
20110299770 | Vaddadi et al. | Dec 2011 | A1 |
20120017240 | Shkedi | Jan 2012 | A1 |
20120054143 | Doig et al. | Mar 2012 | A1 |
20120076357 | Yamamoto et al. | Mar 2012 | A1 |
20120095958 | Pereira et al. | Apr 2012 | A1 |
20120117584 | Gordon | May 2012 | A1 |
20120158511 | Lucero et al. | Jun 2012 | A1 |
20120174155 | Mowrey et al. | Jul 2012 | A1 |
20120177249 | Levy et al. | Jul 2012 | A1 |
20120185566 | Nagasaka | Jul 2012 | A1 |
20120272259 | Cortes | Oct 2012 | A1 |
20120294586 | Weaver et al. | Nov 2012 | A1 |
20120317240 | Wang | Dec 2012 | A1 |
20120324494 | Burger et al. | Dec 2012 | A1 |
20130007191 | Klappert et al. | Jan 2013 | A1 |
20130042262 | Riethmueller | Feb 2013 | A1 |
20130050564 | Adams et al. | Feb 2013 | A1 |
20130054356 | Richman et al. | Feb 2013 | A1 |
20130067523 | Etsuko et al. | Mar 2013 | A1 |
20130070847 | Iwamoto et al. | Mar 2013 | A1 |
20130108173 | Lienhart et al. | May 2013 | A1 |
20130139209 | Urrabazo et al. | May 2013 | A1 |
20130202150 | Sinha et al. | Aug 2013 | A1 |
20130209065 | Yeung | Aug 2013 | A1 |
20130212609 | Sinha et al. | Aug 2013 | A1 |
20130290502 | Bilobrov | Oct 2013 | A1 |
20130297727 | Levy | Nov 2013 | A1 |
20130318096 | Cheung | Nov 2013 | A1 |
20140016696 | Nelson | Jan 2014 | A1 |
20140052737 | Ramanathan et al. | Feb 2014 | A1 |
20140082663 | Neumeier et al. | Mar 2014 | A1 |
20140088742 | Srinivasan | Mar 2014 | A1 |
20140123165 | Mukherjee et al. | May 2014 | A1 |
20140130092 | Kunisetty | May 2014 | A1 |
20140188487 | Perez Gonzalez | Jul 2014 | A1 |
20140193027 | Scherf | Jul 2014 | A1 |
20140195548 | Harron | Jul 2014 | A1 |
20140201769 | Neumeier et al. | Jul 2014 | A1 |
20140201772 | Neumeier et al. | Jul 2014 | A1 |
20140201787 | Neumeier et al. | Jul 2014 | A1 |
20140219554 | Yamaguchi et al. | Aug 2014 | A1 |
20140237576 | Zhang | Aug 2014 | A1 |
20140258375 | Munoz | Sep 2014 | A1 |
20140270489 | Jaewhan et al. | Sep 2014 | A1 |
20140270504 | Baum et al. | Sep 2014 | A1 |
20140270505 | McCarthy | Sep 2014 | A1 |
20140282671 | McMillan | Sep 2014 | A1 |
20140293794 | Zhong et al. | Oct 2014 | A1 |
20140344880 | Geller et al. | Nov 2014 | A1 |
20150026728 | Carter et al. | Jan 2015 | A1 |
20150040074 | Hofmann | Feb 2015 | A1 |
20150100979 | Moskowitz et al. | Apr 2015 | A1 |
20150112988 | Pereira et al. | Apr 2015 | A1 |
20150120839 | Kannan et al. | Apr 2015 | A1 |
20150121409 | Zhang et al. | Apr 2015 | A1 |
20150128161 | Conrad et al. | May 2015 | A1 |
20150163545 | Freed et al. | Jun 2015 | A1 |
20150181311 | Navin et al. | Jun 2015 | A1 |
20150256891 | Kim et al. | Sep 2015 | A1 |
20150302890 | Ergen et al. | Oct 2015 | A1 |
20150382075 | Neumeier et al. | Dec 2015 | A1 |
20160227261 | Neumeier et al. | Aug 2016 | A1 |
20160227291 | Shaw et al. | Aug 2016 | A1 |
20160286244 | Chang et al. | Sep 2016 | A1 |
20160307043 | Neumeier | Oct 2016 | A1 |
20160314794 | Leitman et al. | Oct 2016 | A1 |
20160353172 | Miller et al. | Dec 2016 | A1 |
20160359791 | Zhang et al. | Dec 2016 | A1 |
20170017645 | Neumeier et al. | Jan 2017 | A1 |
20170017651 | Neumeier et al. | Jan 2017 | A1 |
20170017652 | Neumeier et al. | Jan 2017 | A1 |
20170019716 | Neumeier et al. | Jan 2017 | A1 |
20170019719 | Neumeier et al. | Jan 2017 | A1 |
20170026671 | Neumeier et al. | Jan 2017 | A1 |
20170031573 | Kaneko | Feb 2017 | A1 |
20170032033 | Neumeier et al. | Feb 2017 | A1 |
20170032034 | Neumeier et al. | Feb 2017 | A1 |
20170134770 | Neumeier et al. | May 2017 | A9 |
20170186042 | Wong et al. | Jun 2017 | A1 |
20170311014 | Fleischman | Oct 2017 | A1 |
20170353776 | Holden et al. | Dec 2017 | A1 |
Number | Date | Country |
---|---|---|
2 685 450 | Jan 2014 | AL |
2501316 | Sep 2005 | CA |
1557096 | Dec 2004 | CN |
101162470 | Apr 2008 | CN |
1681304 | Jul 2010 | CN |
102377960 | Mar 2012 | CN |
101681373 | Sep 2012 | CN |
248 533 | Aug 1994 | EP |
1578126 | Sep 2005 | EP |
1 760 693 | Mar 2007 | EP |
2 084 624 | Aug 2009 | EP |
2 352 289 | Aug 2011 | EP |
2 541 963 | Jan 2013 | EP |
2457694 | Aug 2009 | GB |
0144992 | Jun 2001 | WO |
2005101998 | Nov 2005 | WO |
2007114796 | Oct 2007 | WO |
2008065340 | Jun 2008 | WO |
2009131861 | Oct 2009 | WO |
2009150425 | Dec 2009 | WO |
2010135082 | Nov 2010 | WO |
2011090540 | Jul 2011 | WO |
2012057724 | May 2012 | WO |
2012108975 | Aug 2012 | WO |
2012170451 | Dec 2012 | WO |
2014142758 | Sep 2014 | WO |
2014145929 | Sep 2014 | WO |
2015100372 | Jul 2015 | WO |
2016123495 | Aug 2016 | WO |
2016168556 | Oct 2016 | WO |
2017011758 | Jan 2017 | WO |
2017011792 | Jan 2017 | WO |
Entry |
---|
International Search Report and Written Opinion dated Mar. 31, 2015 for PCT Application No. PCT/US2014/072255, 8 pages. |
International Search Report and Written Opinion dated Apr. 26, 2016 for PCT Application No. PCT/US2016/015681,13 pages. |
“How to: Watch from the beginning |About DISH” (Dec. 31, 2014) XP055265764, retrieved on Apr. 15, 2016 from URL:http://about.dish.com/blog/hopper/how-watch-beginning 2 pages. |
International Search Report and Written Opinion dated Jun. 24, 2016 for PCT Application No. PCT/US2016/027691, 13 pages. |
Gionis et al., “Similarity Search in High Dimension via Hashing”, Proceedings of the 25th VLDB Conference, 1999, 12 pages. |
Huang , “Bounded Coordinate System Indexing for Real-time Video Clip Search”, Retrieved from the Internet:URL:http://staff.itee.uq.edu.aujzxf/papers/TOIS.pdf, Jan. 1, 2009, 32 pages. |
Kim et al., “Edge-Based Spatial Descriptor Using Color Vector Angle for Effective Image Retrieval”, Modeling Decisions for Artificial Intelligence; [Lecture Notes in Computer Science; Lecture Notes in Artificial Intelligence, Jul. 1, 2005, pp. 365-375. |
Liu et al., “Near-duplicate video retrieval”, ACM Computing Surveys, vol. 45, No. 4, Aug. 30, 2013, pp. 1-23. |
International Search Report and Written Opinion dated Oct. 12, 2016 for PCT Application No. PCT/US2016/042522,13 pages. |
International Search Report and Written Opinion dated Oct. 11, 2016 for PCT Application No. PCT/US2016/042621, 13 pages. |
International Search Report and Written Opinion dated Oct. 20, 2016 for PCT Application No. PCT/US2016/042611,12 pages. |
Scouarnec et al., “Cache policies for cloud-based systems:To keep or not to keep”, 2014 IEEE 7th International Conference on Cloud Computing, IEEE XP032696624, Jun. 27, 2014, pp. 1-8. |
International Search Report and Written Opinion dated Oct. 25, 2016 for PCT Application No. PCT/US2016/042564, 14 pages. |
Anonymous; “Cache (computing)” Wikipedia, the free encyclopedia, URL:http://en.wikipedia.org/w/index.phpti tle=Cache(computing)&oldid=474222804, Jan. 31, 2012; 6 pages. |
International Search Report and Written Opinion dated Oct. 24, 2016 for PCT Application No. PCT/US2016/042557, 11 pages. |
Anil K. Jain, “Image Coding via a Nearest Neighbors Image Model” IEEE Transactions on Communications, vol. Com-23, No. 3, Mar. 1975, pp. 318-331. |
Lee et al., “Fast Video Search Algorithm for Large Video Database Using Adjacent Pixel Intensity Difference Quantization Histogram Feature” International Journal of Computer Science and Network Security, vol. 9, No. 9, Sep. 2009, pp. 214-220. |
Li et al., A Confidence Based Recognition System for TV Commercial Extraction, Conferences in Research and Practice in Information Technology vol. 75, 2008. |
International Search Report and Written Opinion dated Jul. 27, 2011 for PCT Application No. PCT/US2010/057153, 8 pages. |
International Search Report and Written Opinion dated Aug. 31, 2011 for PCT Application No. PCT/US2010/057155, 8 pages. |
International Search Report and Written Opinion dated Aug. 26, 2014 for PCT Application No. PCT/US2014/030782; 11 pages. |
International Search Report and Written Opinion dated Jul. 21, 2014 for PCT Application No. PCT/US2014/030795; 10 pages. |
International Search Report and Written Opinion, dated Jul. 25, 2014 for PCT Application No. PCT/US2014/030805, 10 pages. |
Extended European Search Report dated Mar. 7, 2013 for European Application No. 12178359.1, 8 pages. |
Extended European Search Report dated Oct. 11, 2013 for European Application No. 10844152.8, 19 pages. |
Kabal (P.), Ramachandran (R.P.): The computation of line spectral frequencies using Chebyshev polynomials, IEEE Trans. on ASSP, vol. 34, No. 6, pp. 1419-1426, 1986. |
Itakura (F.): Line spectral representation of linear predictive coefficients of speech signals, J. Acoust. Soc. Amer., vol. 57, Supplement No. 1, S35, 1975, 3 pages. |
Bistritz (Y.), Pellerm (S.): Immittance Spectral Pairs (ISP) for speech encoding, Proc. ICASSP'93, pp. 11-9 to 11-12. |
International Search Report and Written Opinion dated Mar. 8, 2016 for PCT Application No. PCT/ US2015/062945; 9 pages. |
Extended European Search Report dated Dec. 21, 2016 for European Application No. 14763506.4, 11 pages. |
Extended European Search Report dated Nov. 23, 2016 for European Application No. 14764182.3, 10 pages. |
Extended European Search Report dated Jan. 24, 2017 for European Application No. 14762850.7, 12 pages. |
Extended European Search Report dated Jun. 16, 2017, for European Patent Application No. 14873564.0, 8 pages. |
U.S. Appl. No. 14/551,933 , “Final Office Action”, dated May 23, 2016, 19 pages. |
U.S. Appl. No. 14/551,933 , “Non-Final Office Action”, dated Oct. 17, 2016, 15 pages. |
U.S. Appl. No. 14/551,933 , “Non-Final Office Action”, dated Dec. 31, 2015, 24 pages. |
U.S. Appl. No. 14/551,933 , “Notice of Allowance”, dated Mar. 21, 2017, 8 pages. |
U.S. Appl. No. 14/217,039 , “Non-Final Office Action”, dated May 23, 2014, 27 pages. |
U.S. Appl. No. 14/217,039 , “Final Office Action”, dated Nov. 7, 2014, 15 pages. |
U.S. Appl. No. 14/217,039 , “Notice of Allowance”, dated Jan. 29, 2015, 8 pages. |
U.S. Appl. No. 14/678,856 , “Non-Final Office Action”, dated Dec. 1, 2015, 28 pages. |
U.S. Appl. No. 14/678,856 , “Notice of Allowance”, dated May 20, 2016, 9 pages. |
U.S. Appl. No. 14/217,075, “Non-Final Office Action”, dated Jul. 16, 2014, 39 pages. |
U.S. Appl. No. 14/217,075, “Notice of Allowance ”, dated Feb. 20, 2015, 51 pages. |
U.S. Appl. No. 14/217,094, “Notice of Allowance”, dated Sep. 4, 2014, 30 pages. |
U.S. Appl. No. 14/217,375, “Non-Final Office Action”, dated Apr. 1, 2015, 39 pages. |
U.S. Appl. No. 14/217,375, “Notice of Allowance”, dated Apr. 1, 2015, 31 pages. |
U.S. Appl. No. 14/217,425, “Non-Final Office Action”, dated Apr. 7, 2015, 12 pages. |
U.S. Appl. No. 14/217,425, “Notice of Allowance”, dated May 20, 2015, 15 pages. |
U.S. Appl. No. 14/217,435, “Non-Final Office Action”, dated Nov. 24, 2014, 9 pages. |
U.S. Appl. No. 14/217,435, “Notice of Allowance”, dated Jun. 5, 2015, 9 pages. |
U.S. Appl. No. 15/011,099 , “First Action Interview Office Action Summary”, dated May 9, 2017, 6 pages. |
U.S. Appl. No. 15/011,099 , “First Action Interview Pilot Program Pre-Interview Communication”, dated Feb. 28, 2017, 5 pages. |
U.S. Appl. No. 12/788,721 , “Non-Final Office Action”, dated Mar. 28, 2012, 15 Pages. |
U.S. Appl. No. 12/788,721 , “Final Office Action”, dated Aug. 15, 2012, 22 Pages. |
U.S. Appl. No. 12/788,721 , “Notice of Allowance”, dated Aug. 15, 2013, 16 Pages. |
U.S. Appl. No. 14/763,158 , “Non-Final Office Action”, dated Jun. 27, 2016, 16 Pages. |
U.S. Appl. No. 14/763,158 , “ Final Office Action”, dated Sep. 7, 2016, 12 Pages. |
U.S. Appl. No. 14/763,158 , “Notice of Allowance”, dated Mar. 17, 2016, 8 Pages. |
U.S. Appl. No. 14/807,849 , “Non-Final Office Action”, dated Nov. 25, 2015, 12 Pages. |
U.S. Appl. No. 14/807,849 , “Final Office Action”, dated Apr. 19, 2016, 13 pages. |
U.S. Appl. No. 14/807,849 , “Non-Final Office Action”, dated Feb. 28, 2017, 10 Pages. |
U.S. Appl. No. 14/089,003 , “Notice of Allowance”, dated Jul. 30, 2014, 24 Pages. |
U.S. Appl. No. 12/788,748 , “Non-Final Office Action”, dated Jan. 10, 2013, 10 Pages. |
U.S. Appl. No. 12/788,748 , “Final Office Action”, dated Nov. 21, 2013, 13 Pages. |
U.S. Appl. No. 12/788,748 , “Notice of Allowance”, dated Mar. 6, 2014, 7 Pages. |
U.S. Appl. No. 14/953,994 , “Non-Final Office Action”, dated Mar. 3, 2016, 34 Pages. |
U.S. Appl. No. 14/953,994 , “Final Office Action”, dated Jun. 1, 2016, 36 Pages. |
U.S. Appl. No. 14/953,994 , “Notice of Allowance”, dated Aug. 31, 2016, 15 Pages. |
U.S. Appl. No. 14/807,849 , “Final Office Action”, dated Jun. 22, 2017, 10 pages. |
U.S. Appl. No. 15/011,099 , “Final Office Action”, dated Jul. 24, 2017, 22 pages. |
U.S. Appl. No. 15/240,801 , “Non-Final Office Action”, dated Aug. 11, 2017, 18 pages. |
U.S. Appl. No. 15/240,815 , “Non-Final Office Action”, dated Aug. 23, 2017, 15 pages. |
U.S. Appl. No. 15/211,345 , “First Action Interview Pilot Program Pre-Interview Communication”, dated Sep. 19, 2017, 8 pages. |
U.S. Appl. No. 14/807,849 , “Notice of Allowance”, dated Nov. 30, 2017, 9 Pages. |
U.S. Appl. No. 15/240,801 , “Final Office Action”, dated Dec. 22, 2017, 24 pages. |
U.S. Appl. No. 15/011,099, “Non-Final Office Action”, dated Jan. 22, 2018, 23 pages. |
U.S. Appl. No. 15/240,815 , “Final Office Action”, dated Mar. 2, 2018, 14 pages. |
U.S. Appl. No. 15/211,345 , “Final Office Action”, dated Mar. 2, 2018, 14 pages. |
Extended European Search Report dated Mar. 22, 2018 for European Application No. 15865033.3, 10 pages. |
U.S. Appl. No. 15/099,842 , “Final Office Action”, dated Apr. 2, 2018, 8 pages. |
U.S. Appl. No. 15/210,730, “Notice of Allowance”, dated May 23, 2018, 10 pages. |
U.S. Appl. No. 15/796,692, “Non-Final Office Action”, dated Jun. 6, 2018, 20 pages. |
U.S. Appl. No. 15/011,099, “Notice of Allowance”, dated Jun. 28, 2018, 12 pages. |
U.S. Appl. No. 15/796,706, “Non-Final Office Action”, dated Jun. 26, 2018, 17 pages. |
U.S. Appl. No. 15/240,801, “Notice of Allowance”, dated Aug. 30, 2018, 9 pages. |
U.S. Appl. No. 15/211,345, “Non-Final Office Action”, dated Sep. 4, 2018, 13 pages. |
U.S. Appl. No. 15/099,842, “Notice of Allowance”, dated Sep. 7, 2018, 10 pages. |
U.S. Appl. No. 15/240,815, “Notice of Allowance”, dated Sep. 12, 2018, 9 pages. |
Number | Date | Country | |
---|---|---|---|
20180054658 A1 | Feb 2018 | US |
Number | Date | Country | |
---|---|---|---|
61920086 | Dec 2013 | US |
Number | Date | Country | |
---|---|---|---|
Parent | 14763158 | US | |
Child | 15796698 | US |
Number | Date | Country | |
---|---|---|---|
Parent | 14551933 | Nov 2014 | US |
Child | 14763158 | US |