Patent Application
20150006667
The present disclosure relates to data compression, and more particularly, to a system for dynamically compressing data based on analyzing the data content and/or participating devices.
Modern computing technology is increasingly becoming reliant upon communications for basic operation. In addition to the communication-related functionality that is typically included in mobile devices (e.g., voice/text communication, media, streaming, etc.), this trend is at least in part due to the general architecture utilized in modern computing devices becoming less device-centric. In a previous example of operation, physical media was employed to install applications configured to execute locally (e.g., in an offline mode). Sometimes the local applications would need to access an online resource. While this type of operation may still be employed, emerging computing devices are quickly moving towards an always-connected mode of operation. Some or all of the programmatic elements making up the applications executed by the new computing devices may now be located remotely. In one example implementation, “cloud”-based resources may comprise at least one computing device accessible via a wide-area network (WAN). Parts of applications may be stored in the cloud (e.g., databases, models, etc.) so that information may be available in real-time, while also reducing the processing load of the local computing device.
While always-on architectures may satisfy user desires from a performance perspective, increasing the communication load introduces a myriad of other problems. At the device level, increased communication requirements may result in more data being transmitted and received, which puts more strain on the processing, communication and energy resources of devices. The additional loading is most problematic for computing devices that rely substantially on wireless communication (e.g., smart phones). Moreover, the wired/wireless communication mediums on which these devices rely are being taxed by the additional communication requirements. More users are utilizing more devices with higher communication demands. As a result, traffic is increasing, and management of the increased traffic will be an issue for the foreseeable future.
Features and advantages of various embodiments of the claimed subject matter will become apparent as the following Detailed Description proceeds, and upon reference to the Drawings, wherein like numerals designate like parts, and in which:
Although the following Detailed Description will proceed with reference being made to illustrative embodiments, many alternatives, modifications and variations thereof will be apparent to those skilled in the art.
This disclosure is directed to a dynamic data compression system. A device may interact with a remote resource such as at least one cloud-based computing device. In a first example of operation, the device may request data comprising certain content from the remote resource. The remote resource may determine if any part of the requested content is identical or similar to content in other data, and if identical or similar content exists, if the identical or similar content is already on the requesting device. If other data with identical or similar content is determined to be on the requesting device, smart compression may be performed by transmitting only the portions of the requested content not already residing on the requesting device. During decompression the requesting device may then combine the portions of the content received from the remote resource with the content already existing on the device. In another example of smart compression, a device may capture at least one of an image or video, and may perform smart compression by transmitting only certain features of the image or video to the remote resource. The remote resource may then perform decompression by determining the content of the image based on the features, and may perform an action based on the determined content (e.g., may transmit information to the capturing device). In addition, a determination whether to perform smart compression may be based on system/device conditions.
In one embodiment, at least one device may comprise, for example, a content analytics module, a device analytics module, a smart compression/decompression (codec) module and a communication module. The content analytics module may be to receive a request for data including certain content from a device and to analyze the content of the data. The device analytics module may be to analyze characteristics of the requesting device based at least on the content analysis performed by the content analytics module. The smart codec module may be to at least compress the data based at least on the analysis performed by the client analytics module. The communication module may be to transmit the compressed data to the requesting device.
In an example implementation consistent with the present disclosure, the at least one device may comprise a plurality of computing devices to operate as a cloud resource accessible via a wide area network (WAN). The content analytics module being to analyze the content of the data requested by the device may comprise, for example, the content analytics module being to determine if any portion of the content is identical or similar to any portion of content in other data. The device analytics module being to analyze the characteristics of the requesting device may comprise, for example, the device analytics module being to, if it is determined that a portion of the content is identical or similar to any portion of content in other data, determine if the requesting device is able to support smart compression. Determining if the requesting device is able to perform smart compression may comprise, for example, the device analytics module being to determine at least one of capability or condition for the requesting device. The device analytics module being to analyze the characteristics of the requesting device may comprise, for example, the device analytics module being to determine if the other data determined to contain any portion of identical or similar content is already present on the requesting device. The smart codec module being to at least compress the data may comprise, for example, the smart codec module being to remove any portion of content from the data that was determined to be identical or similar to any portion of content in the other data determined to be already present in the requesting device. In another example implementation, the smart codec module being to at least compress the data may comprise, for example, the smart codec module being to generate change information allowing the requesting device to alter the content of the other data determined to be already present in the requesting device to be identical or similar to the content of the data.
In one embodiment, the smart codec may further be to receive compressed data from a capturing device, the compressed data including features derived from at least one of images or video captured by the capturing device. The smart codec may further be to determine content for the at least one of images or video based on the features. In the same or a different embodiment the at least one device may further comprise an augmented reality module to provide context information to the capturing device based on the content. An example method consistent with the present disclosure may comprise receiving a request for data including certain content from a device, performing analysis on the content of the data, performing analysis on the requesting device based at least on the content analysis, determining whether to use smart compression based at least on the device analysis, compressing the data based on at least on the determination whether to use smart compression and the device analysis and transmitting the compressed data to the requesting device.
Device 102 may interact with remote resource 104 via wired/wireless communication. In one example of operation, device 102 may transmit a request for content (e.g., for data including certain content) to remote resources 104, to which remote resources 104 may respond with the requested content. It may also be possible for device 102 may also provide remote resources 104 with image and/or video information, to which remote resources 104 may respond with context information pertaining the image and/or video information. While these examples of operation are discussed in detail in this disclosure, they are presented only for the sake of explanation and are not intended to limit the applicability of embodiments consistent with the present disclosure. In particular, embodiments consistent with the present disclosure may be applied in any situation where data compression would be advantageous for the transmission of data between devices.
In one embodiment, device 102 may comprise, for example, a smart codec module 106. A smart codec module may comprise, for example, a codec with enhanced compression features such as will be described in regard to
Device 102′ may comprise system module 200 configured to manage device operations. System module 200 may include, for example, processing module 202, memory module 204, power module 206, user interface module 208 and communication interface module 210 that may be configured to interact with communication module 212. Device 102′ may also include smart codec module 106′ configured to interact with at least user interface module 208 and communication module 212. While communication module 212 and smart codec module 106′ are illustrated as separate from system module 200, this is merely for the sake of explanation herein. Some or all of the functionality associated with communication module 212 and/or smart codec module 106′ may also be incorporated within system module 200.
In device 102′, processing module 202 may comprise one or more processors situated in separate components, or alternatively, may comprise one or more processing cores embodied in a single component (e.g., in a System-on-a-Chip (SoC) configuration) and any processor-related support circuitry (e.g., bridging interfaces, etc.). Example processors may include, but are not limited to, various x86-based microprocessors available from the Intel Corporation including those in the Pentium, Xeon, Itanium, Celeron, Atom, Core i-series product families, Advanced RISC (e.g., Reduced Instruction Set Computing) Machine or “ARM” processors, etc. Examples of support circuitry may include chipsets (e.g., Northbridge, Southbridge, etc. available from the Intel Corporation) configured to provide an interface through which processing module 202 may interact with other system components that may be operating at different speeds, on different buses, etc. in device 102′. Some or all of the functionality commonly associated with the support circuitry may also be included in the same physical package as a microprocessor (e.g., in an SoC package like the Sandy Bridge integrated circuit available from the Intel Corporation).
Processing module 202 may be configured to execute various instructions in device 102′. Instructions may include program code configured to cause processing module 202 to perform activities related to reading data, writing data, processing data, formulating data, converting data, transforming data, etc. Information (e.g., instructions, data, etc.) may be stored in memory module 204. Memory module 204 may comprise random access memory (RAM) and/or read-only memory (ROM) in a fixed or removable format. RAM may include memory configured to hold information during the operation of device 102′ such as, for example, static RAM (SRAM) or Dynamic RAM (DRAM). ROM may include memories such as bios memory configured to provide instructions when device 102′ activates in the form of bios, Unified Extensible Firmware Interface (UEFI), etc., programmable memories such as electronic programmable ROMs (EPROMS), Flash, etc. Other fixed and/or removable memory may include magnetic memories such as, for example, floppy disks, hard drives, etc., electronic memories such as solid state flash memory (e.g., embedded multimedia card (eMMC), etc.), removable memory cards or sticks (e.g., micro storage device (uSD), USB, etc.), optical memories such as compact disc-based ROM (CD-ROM), etc. Power module 206 may include internal power sources (e.g., a battery) and/or external power sources (e.g., electromechanical or solar generator, power grid, fuel cell, etc.), and related circuitry configured to supply device 102′ with the power needed to operate.
User interface module 208 may include circuitry configured to allow users to interact with device 102′ such as, for example, various input mechanisms (e.g., microphones, switches, buttons, knobs, keyboards, speakers, touch-sensitive surfaces, one or more sensors configured to capture images and/or sense proximity, distance, motion, gestures, etc.) and output mechanisms (e.g., speakers, displays, lighted/flashing indicators, electromechanical components for vibration, motion, etc.). Communication interface module 210 may be configured to handle packet routing and other control functions for communication module 212, which may include resources configured to support wired and/or wireless communications. Wired communications may include serial and parallel wired mediums such as, for example, Ethernet, Universal Serial Bus (USB), Firewire, Digital Visual Interface (DVI), High-Definition Multimedia Interface (HDMI), etc. Wireless communications may include, for example, close-proximity wireless mediums (e.g., radio frequency (RF) such as based on the Near Field Communications (NFC) standard, infrared (IR), optical character recognition (OCR), magnetic character sensing, etc.), short-range wireless mediums (e.g., Bluetooth, wireless local area networking (WLAN), Wi-Fi, etc.) and long range wireless mediums (e.g., cellular wide area radio communication technology that may include, for example, a Global System for Mobile Communications (GSM) radio communication technology, a General Packet Radio Service (GPRS) radio communication technology, an Enhanced Data Rates for GSM Evolution (EDGE) radio communication technology, and/or a Third Generation Partnership Project (3GPP) radio communication technology (e.g. UMTS (Universal Mobile Telecommunications System), FOMA (Freedom of Multimedia Access), 3GPP LTE (Long Term Evolution), 3GPP LTE Advanced (Long Term Evolution Advanced)), CDMA2000 (Code division multiple access 2000), CDPD (Cellular Digital Packet Data), Mobitex, 3G (Third Generation), CSD (Circuit Switched Data), HSCSD (High-Speed Circuit-Switched Data), UMTS (3G) (Universal Mobile Telecommunications System (Third Generation)), W-CDMA (UMTS) (Wideband Code Division Multiple Access (Universal Mobile Telecommunications System)), HSPA (High Speed Packet Access), HSDPA (High-Speed Downlink Packet Access), HSUPA (High-Speed Uplink Packet Access), HSPA+ (High Speed Packet Access Plus), UMTS-TDD (Universal Mobile Telecommunications System-Time-Division Duplex), TD-CDMA (Time Division-Code Division Multiple Access), TD-CDMA (Time Division-Synchronous Code Division Multiple Access), 3GPP Rel. 8 (Pre-4G) (3rd Generation Partnership Project Release 8 (Pre-4th Generation)), 3GPP Rel. 9 (3rd Generation Partnership Project Release 9), 3GPP Rel. 10 (3rd Generation Partnership Project Release 10), 3GPP Rel. 11 (3rd Generation Partnership Project Release 11), 3GPP Rel. 12 (3rd Generation Partnership Project Release 12), UTRA (UMTS Terrestrial Radio Access), E-UTRA (Evolved UMTS Terrestrial Radio Access), LTE Advanced (4G) (Long Term Evolution Advanced (4th Generation)), cdmaOne (2G), CDMA2000 (3G) (Code division multiple access 2000 (Third generation)), EV-DO (Evolution-Data Optimized or Evolution-Data Only), AMPS (1G) (Advanced Mobile Phone System (1st Generation)), TACS/ETACS (Total Access Communication System/Extended Total Access Communication System), D-AMPS (2G) (Digital AMPS (2nd Generation)), PTT (Push-to-talk), MTS (Mobile Telephone System), IMTS (Improved Mobile Telephone System), AMTS (Advanced Mobile Telephone System), OLT (Norwegian for Offentlig Landmobil Telefoni, Public Land Mobile Telephony), MTD (Swedish abbreviation for Mobiltelefonisystem D, or Mobile telephony system D), Autotel/PALM (Public Automated Land Mobile), ARP (Finnish for Autoradiopuhelin, “car radio phone”), NMT (Nordic Mobile Telephony), Hicap (High capacity version of NTT (Nippon Telegraph and Telephone)), CDPD (Cellular Digital Packet Data), Mobitex, DataTAC, iDEN (Integrated Digital Enhanced Network), PDC (Personal Digital Cellular), CSD (Circuit Switched Data), PHS (Personal Handy-phone System), WiDEN (Wideband Integrated Digital Enhanced Network), iBurst, Unlicensed Mobile Access (UMA, also referred to as also referred to as 3GPP Generic Access Network, or GAN standard). In one embodiment, communication interface module 210 may be configured to prevent wireless communications that are active in communication module 212 from interfering with each other. In performing this function, communication interface module 210 may schedule activities for communication module 212 based on, for example, the relative priority of messages awaiting transmission.
In the embodiment illustrated in
System module 200′ may comprise processing module 202, memory module 204, power module 206 and communications interface module 210 to interact with communication module 212. These modules may operate in a manner similar to that already disclosed in regard to
Remote resource 104′ may further comprise smart codec 108′, device analytics module 110′ and content analytics module 112′. Smart codec 108′ may interact with at least device analytics module 110′ and communications module 212. For example, smart codec 108′ may receive data comprising certain content requested by device 102, may compress the data and then may provide the compressed data to communication module 212 for transmission to device 102. Device analytics modules 110′ may interact with at least smart codec 108′ and content analytics module 112′. For example, device analytics module 110′ may receive at least an identification of other data including portions of content identical or similar to portions of the content of data requested by device 102 from content analytics module 112′, may determine if any of the other data is already stored in device 102 and may provide data for compression to smart codec module 108′ based on the identification of the other data already stored in device 102. Content analytics module 112′ may interact with at least content analytics module 112′ and processing module 202. For example, content analytics module may use processing module 202 to determine any other data having portions of content identical or similar to portions of content in data being requested by device 102, and may provide an identification of the other data to device analytics module 110′.
In one embodiment, smart codec module 108′ may also interact directly with processing module 202. For example, smart codec module 108′ may receive compressed data from device 102 and may proceed to decompress the compressed data. The decompressed data may include, for example, features corresponding to data captured by device 102. Processing module 102 may be utilized to determine content corresponding to the captured data based on the features, and further to generate a response to device 102 based on the content determined from the features.
Initially, examples of content include, but are not limited to, audio information such as music, concerts, speeches, lectures, radio programs, audio coverage of special events, etc., and images/video information such as television programs, movies, presentations, speeches, video coverage of special events, etc. An example of requested data 400 being compared to other data 402 is illustrated in
After receiving compressed data 408, smart codec 108 in device 102 may be able to separate the compressed data back into portions as shown at 410 and determine the identical or similar portions of content in data already existing on device 102 as shown at 412. The two sets of data may then be combined at 414 to create data equivalent to requested data 400. The manipulation of data shown at 410 and 412 may be based on, for example, information generated during smart compression. For example, remote resources 104 may generate assembly information or another type of data to indicate the portions of data already on device 102 that need to be combined with compressed data 410 to arrive at requested data 400. For example, information generated during smart compression may indicate that frames XXX-YYY from data ZZZ already stored in device 102 should be inserted into compressed data 410 at one or more places to decompress the data.
In an alternative implementation usable alone or in conjunction with example disclosed in
Initially, device 102 may capture information as shown at 500. For example, captured information 502 may include at least one of images or video captured by a camera in device 102. In existing systems all of the captured information is transmitted to remote resources 104, which may necessitate the transmission of a substantial amount of data even after existing compression schemes are applied. Instead, in smart compression only certain features 504 of information 502 may be transmitted, which entails substantially less data. Examples of features 504 that may be captured include, but are not limited to, indicia of location (e.g., street signs), structural features, colors/patterns/textures, relative locations of visually distinctive objects (e.g., windows, doors, awnings, roofs, etc.), light/dark differential, etc. Features 504 of information 502 may then be compressed as illustrated 506 and transmitted to remote resource 104 as shown at 508. In one embodiment, compressed data 508 may be compressed even further using existing techniques for data compression as known in the art.
Remote resources 104 may then analyze compressed data 508 as shown at 510. In the example disclosed in
In operation 606 a determination may then be made as to whether smart compression should be used to compress the requested data. Referring to the analysis performed in operations 602 and 604, smart compression may not be employed if, for example, smart compression is not supported by the device, if the device does not have adequate resources to support the additional processing load required for smart compression, if no other data comprising portions of content identical or similar to portions of the requested content was determined to be already stored on the device, etc. If in operation 606 it is determined that smart compression should not be utilized, then in operation 608 the entirety of the requested content may be provided to the device. If in operation 606 it is determined that smart compression should be utilized, then in operation 610 the data may be compressed based on the content and device analytics. For example, portions of content in the requested data that were determined to not already be stored in device 100 (e.g., “new” content) may be selected, compressed, and then transmitted to the device in operation 612.
In operation 706 a determination may then be made as to whether to utilize smart compression based on, for example, the determined condition of the device. If in operation 704 it is determined that smart compression should not be utilized (e.g., due to limited resources being available in the device), then in operation 706 the entirety of the captured data may be provided to a remote resource for processing. If in operation 704 it is determined that smart compression should be employed, then in operation 708 feature analytics may be performed. For example, certain features may be extracted from the captured data that may be indicative of the content of the captured. Smart compression may then occur in operation 710 wherein the extracted features are then collected for transmission to the remote resource in operation 712.
While
As used in this application and in the claims, a list of items joined by the term “and/or” can mean any combination of the listed items. For example, the phrase “A, B and/or C” can mean A; B; C; A and B; A and C; B and C; or A, B and C. As used in this application and in the claims, a list of items joined by the term “at least one of” can mean any combination of the listed terms. For example, the phrases “at least one of A, B or C” can mean A; B; C; A and B; A and C; B and C; or A, B and C.
As used in any embodiment herein, the term “module” may refer to software, firmware and/or circuitry configured to perform any of the aforementioned operations. Software may be embodied as a software package, code, instructions, instruction sets and/or data recorded on non-transitory computer readable storage mediums. Firmware may be embodied as code, instructions or instruction sets and/or data that are hard-coded (e.g., nonvolatile) in memory devices. “Circuitry”, as used in any embodiment herein, may comprise, for example, singly or in any combination, hardwired circuitry, programmable circuitry such as computer processors comprising one or more individual instruction processing cores, state machine circuitry, and/or firmware that stores instructions executed by programmable circuitry. The modules may, collectively or individually, be embodied as circuitry that forms part of a larger system, for example, an integrated circuit (IC), system on-chip (SoC), desktop computers, laptop computers, tablet computers, servers, smartphones, etc.
Any of the operations described herein may be implemented in a system that includes one or more storage mediums having stored thereon, individually or in combination, instructions that when executed by one or more processors perform the methods. Here, the processor may include, for example, a server CPU, a mobile device CPU, and/or other programmable circuitry. Also, it is intended that operations described herein may be distributed across a plurality of physical devices, such as processing structures at more than one different physical location. The storage medium may include any type of tangible medium, for example, any type of disk including hard disks, floppy disks, optical disks, compact disk read-only memories (CD-ROMs), compact disk rewritables (CD-RWs), and magneto-optical disks, semiconductor devices such as read-only memories (ROMs), random access memories (RAMs) such as dynamic and static RAMs, erasable programmable read-only memories (EPROMs), electrically erasable programmable read-only memories (EEPROMs), flash memories, Solid State Disks (SSDs), embedded multimedia cards (eMMCs), secure digital input/output (SDIO) cards, magnetic or optical cards, or any type of media suitable for storing electronic instructions. Other embodiments may be implemented as software modules executed by a programmable control device.
Thus, this disclosure is directed to a dynamic data compression system. A device may request data comprising certain content from a remote resource. The remote resource may determine if any part of the content is identical or similar to content in other data and if the other data is already on the requesting device. Smart compression may then involve transmitting only the portions of the content not residing on the requesting device, which may combine the received portions of the content with the other data. In another example, a capturing device may capture at least one of an image or video. Smart compression may then involve transmitting only certain features of the image/video to the remote resource. The remote resource may determine image/video content based on the received features, and may perform an action based on the content. In addition, a determination whether to perform smart compression may be based on system/device conditions.
The following examples pertain to further embodiments. The following examples of the present disclosure may comprise subject material such as a device, a method, at least one machine-readable medium for storing instructions that when executed cause a machine to perform acts based on the method, means for performing acts based on the method and/or a dynamic data compression system, as provided below.
According to this example there is provided at least one device. The at least one device may include a content analytics module to receive a request for data including certain content from a device and to analyze the content of the data, a device analytics module to analyze characteristics of the requesting device based at least on the content analysis performed by the content analytics module, a smart compression/decompression (codec) module to at least compress the data based at least on the analysis performed by the client analytics module and a communication module to transmit the compressed data to the requesting device.
This example includes the elements of example 1, wherein the at least one device comprises a plurality of computing devices to operate as a cloud resource accessible via a wide area network (WAN).
This example includes the elements of example 2, wherein the plurality of computing devices are servers, at least one the plurality of servers being to store the requested data including certain content.
This example includes the elements of any of examples 1 to 3, wherein the requesting device comprises at least a smart codec compatible with the smart codec in the at least one device.
This example includes the elements of any of examples 1 to 4, wherein the content analytics module being to analyze the content of the data requested by the device comprises the content analytics module being to determine if any portion of the content is identical or similar to any portion of content in other data.
This example includes the elements of example 5, wherein the device analytics module being to analyze the characteristics of the requesting device comprises the device analytics module being to, if it is determined that a portion of the content is identical or similar to any portion of content in other data, determine if the requesting device is able to support smart compression.
This example includes the elements of example 6, wherein the device analytics module being to determine if the requesting device is able to perform smart compression comprises the device analytics module being to determine at least one of capability or condition for the requesting device.
This example includes the elements of any of examples 5 to 7, wherein the device analytics module being to analyze the characteristics of the requesting device comprises the device analytics module being to track other data already present on the requesting device.
This example includes the elements of any of examples 5 to 8, wherein the device analytics module being to analyze the characteristics of the requesting device comprises the device analytics module being to determine if the other data determined to contain any portion of identical or similar content is already present on the requesting device.
This example includes the elements of example 9, wherein the smart codec module being to at least compress the data comprises the smart codec module being to remove any portion of content from the data that was determined to be identical or similar to any portion of content in the other data determined to be already present in the requesting device.
This example includes the elements of any of examples 9 to 10, wherein the smart codec module being to at least compress the data comprises the smart codec module being to generate change information allowing the requesting device to alter the content of the other data determined to be already present in the requesting device to be identical or similar to the content of the data.
This example includes the elements of example 11, wherein the change information comprises at least instructions for altering other content already present in the requesting device.
This example includes the elements of any of examples 1 to 12, wherein the smart codec is further to receive compressed data from a capturing device, the compressed data including features derived from at least one of images or video captured by the capturing device.
This example includes the elements of example 13, wherein the smart codec is further to determine content for the at least one of images or video based on the features.
This example includes the elements of example 14, further comprising an augmented reality module to provide context information to the capturing device based on the content.
This example includes the elements of example 15, wherein the context information comprises descriptive information corresponding to at least one of the features.
According to this example there is provided a device. The device may include a user interface module to cause at least one of images or video to be captured, a smart codec to generate compressed data by deriving features from the at least one of images or video, the compressed data including at least the derived features and a communication module to transmit the compressed data to remote resources.
This example includes the elements of example 17, wherein the smart codec module is further to determine device condition and determine whether to use smart compression based on the device condition.
This example includes the elements of any of examples 17 to 18, wherein the communication module is further to receive context information from the remote resources, the context information corresponding to the at least one of images or video.
This example includes the elements of example 18, wherein the user interface module is further to display the received context information superimposed over a display of the at least one of images or video.
According to this example there is provided a method. The method may include receiving a request for data including certain content from a device, performing analysis on the content of the data, performing analysis on the requesting device based at least on the content analysis, determining whether to use smart compression based at least on the device analysis, compressing the data based on at least on the determination whether to use smart compression and the device analysis and transmitting the compressed data to the requesting device.
This example includes the elements of example 21, wherein performing analysis on the content of the data comprises determining if any portion of the content is identical or similar to any portion of content in other data.
This example includes the elements of example 22, wherein performing analysis on the requesting device comprises tracking the other data already present on the requesting device.
This example includes the elements of example 23, wherein performing analysis on the requesting device comprises determining if the other data determined to contain any portion of identical or similar content is already present in the requesting device.
This example includes the elements of any of examples 22 to 24, wherein if it is determined to use smart compression, compressing the data comprises removing any portion of content from the data that was determined to be identical or similar to any portion of content in the other data determined to be already present on the requesting device.
This example includes the elements of example 25, wherein if it is determined to use smart compression, compressing the data comprises generating change information allowing the requesting device to alter the content of the other data determined to be already present in the requesting device to be identical or similar to the content of the data.
This example includes the elements of any of examples 25 to 26, wherein determining whether to use smart compression comprises determining at least one of capability or condition for the requesting device.
This example includes the elements of any of examples 21 to 27, further comprising receiving compressed data from a capturing device, the compressed data including features derived from at least one of images or video captured by the capturing device and determining content for the at least one of images or video based on the features.
This example includes the elements of example 28, further comprising providing context information to the capturing device based on the content.
According to this example there is provided a method. The method may include capturing at least one of images or video, compressing data by deriving features from the at least one of images or video, the compressed data including at least the derived features and transmitting the compressed data to remote resources.
This example includes the elements of example 29, further comprising determining device condition and determining whether to use smart compression based on the device condition.
This example includes the elements of any of examples 29 to 30, further comprising receiving context information from the remote resources, the context information corresponding to the at least one of images or video.
This example includes the elements of example 32, further comprising displaying the received context information superimposed over a display of the at least one of images or video.
This example includes a system comprising at least one device, the system being arranged to perform the method of any of examples 21 to 33.
This example includes a chipset arranged to perform the method of any of examples 21 to 33.
This example includes at least one machine readable medium comprising a plurality of instructions that, in response to be being executed on a computing device, cause the computing device to carry out the method according to any of examples 21 to 33.
This example includes at least one device configured for use with a dynamic data compression system, the device being arranged to perform the method of any of examples 21 to 33.
This example includes at least one device having means to perform the method of any of examples 21 to 33.
The terms and expressions which have been employed herein are used as terms of description and not of limitation, and there is no intention, in the use of such terms and expressions, of excluding any equivalents of the features shown and described (or portions thereof), and it is recognized that various modifications are possible within the scope of the claims. Accordingly, the claims are intended to cover all such equivalents.
