MLchartDataset catalogue

Patent · US9888105B2 · B2 · US

Intuitive computing methods and systems

(11) Publication number
US9888105B2
(21) Application number
15/467,819
(22) Filing date
2017-03-23
(30) Priority date
2009-10-28
(43) Publication date
2018-02-06
(45) Date of grant
2018-02-06
(51) IPC
G01C 21/20; G01C 21/36; H04M 1/724; H04M 1/72403; H04N 23/80; G01C 21/00; G06F 3/00; G06F 3/01; G06F 3/023; G06F 3/0481; G06F 3/0484; G06F 3/0488; G06K 9/62; G06Q 10/10; G06T 19/00; G09G 5/00; H04W 4/02
(52) CPC
  • H04W Wireless communication networks: 4/02, 4/024, 4/027, 4/029, 88/02
  • G01C Measuring distances, levels or bearings; surveying; navigation; gyroscopic instruments; photogrammetry or videogrammetry: 21/00, 21/20, 21/36
  • G06F Electric digital data processing: 18/24, 3/005, 3/011, 3/017, 3/023, 3/04817, 3/0482, 3/04842, 3/04847, 3/04886
  • G06K Graphical data reading; presentation of data; record carriers; handling record carriers: 9/00671, 9/62, 9/6267
  • G06Q Information and communication technology [ICT] specially adapted for administrative, commercial, financial, managerial or supervisory purposes; systems or methods specially adapted for administrative, commercial, financial, managerial or supervisory purposes, not otherwise provided for: 10/10
  • G06T Image data processing or generation, in general: 19/006, 2200/24
  • G06V Image or video recognition or understanding: 20/20
  • G09G Arrangements or circuits for control of indicating devices using static means to present variable information: 5/00
  • H04M Telephonic communication: 1/724, 1/72403, 1/72519, 1/72522, 2250/22, 2250/74
  • H04N Pictorial communication, e.g. television: 23/667, 23/80, 5/225, 5/23229, 5/23245
(73) Assignee
Digimarc Corp
(72) Inventors
Geoffrey B. Rhoads
(54) Title
Intuitive computing methods and systems
(57) Abstract

A smart phone senses audio, imagery, and/or other stimulus from a user's environment, and acts autonomously to fulfill inferred or anticipated user desires. In one aspect, the detailed technology concerns phone-based cognition of a scene viewed by the phone's camera. Recognition tasks, selected with the aid of context, are allocated increased or decreased resources based on data comprising (a) user input data indicating express or implied encouragement or discouragement of the recognition task and/or (b) a detection state metric, representing a quantified likelihood that the recognition goal sought by the recognition task will be reached. A great number of other features and arrangements are also detailed.

Full text
View on Google Patents

Claims (20)

  1. An image processing method comprising the acts: capturing imagery with a camera portion of a mobile system, the system also including a processor controlled by configuration instructions stored in a memory; selecting a first recognition process to apply to the captured imagery, from among several recognition processes that the system is equipped to apply, said selection of the first recognition process being based on context information rather than on express user instruction; launching the selected first recognition process, employing said processor, to discern information about a subject depicted in the captured imagery; receiving first data, after said selected first recognition process has been launched, said first data comprising (a) user input data indicating express or implied user encouragement or discouragement of said first recognition process by the user, and/or (b) a detection state metric, representing a quantified likelihood that a recognition goal sought by the first recognition process will be reached; and allocating increased or decreased resources to said first recognition process based on said received first data, said allocation of increased resources being apart from increased resource usage due to any increasing base complexity of successive stages of the selected first recognition process.
  2. The method of claim 1 in which the received first data comprises user input data indicating user encouragement of said process, and the method includes allocating increased resources to said first recognition process based on said indication of encouragement, wherein the mobile system seems to respond intuitively to a user interest in said subject.
  3. The method of claim 1 in which the received first data indicates comprises user input data indicating user discouragement of said process, and the method includes allocating reduced resources to said first recognition process based on said indication of discouragement, wherein the mobile system seems to respond intuitively to a user dis-interest in said subject.
  4. The method of claim 1 in which the received first data comprises a detection state metric representing a quantified likelihood that the recognition goal sought by the first recognition process will be reached, and the method includes allocating increased resources to the first recognition process as a consequence of said detection state metric.
  5. The method of claim 1 in which the received first data comprises a detection state metric representing a quantified likelihood that the recognition goal sought by the first recognition process will be reached, and the method includes allocating decreased resources to the first recognition process as a consequence of said detection state metric.
  6. The method of claim 1 that includes: receiving user data indicating express or implied user encouragement or discouragement of the first recognition process; and receiving a detection state metric representing a quantified likelihood that the recognition goal sought by the first recognition process will be reached; wherein the method includes allocating resources to said first recognition process based on both (1) said received user data; and (2) said received detection state metric.
  7. The method of claim 1 in which the context information on which selection of the first recognition process is based, comprises image information.
  8. The method of claim 7 that includes selecting said first recognition process, from the several recognition processes the system is equipped to apply, based on results of baseline image processing operations applied to the captured imagery.
  9. The method of claim 7 that includes selecting said first recognition process, from the several recognition processes the system is equipped to apply, also based on context data distinct from image data.
  10. The method of claim 7 in which the context information on which selection of the first recognition process is based, also comprises location information.
  11. The method of claim 1 in which the context information on which selection of the first recognition process is based, comprises location information.
  12. The method of claim 1 that includes selecting said first recognition process, from the several recognition processes the system is equipped to apply, based on context data distinct from image data.
  13. The method of claim 1 that includes: selecting both first and second recognition processes to apply to the captured imagery, from among said several recognition processes the system is equipped to apply, based on context information rather than on express user instruction; launching both the first and second recognition processes; receiving second data, after said second recognition process has been launched, said second data comprising (a) user input data indicating express or implied user encouragement or discouragement of said second recognition process by the user, and/or (b) a detection state metric, representing a quantified likelihood that a recognition goal sought by the second recognition process will be reached; and based on the received first and second data, allocating increased resources to the first recognition process, and allocating reduced resources to the second recognition process.
  14. The method of claim 1 in which allocating increased resources to said first recognition process comprises making GPU resources available instead of CPU resources, allocating more scratchpad memory for calculations, allowing access to faster-responding memory, allowing increased power consumption, or allowing access to a faster network connection.
  15. A non-transitory computer readable storage medium containing software instructions to configure a mobile system, equipped with a processor and a camera, to perform acts including: selecting a first recognition process to apply to imagery captured by the camera, from among several recognition processes that the system is equipped to apply, said selection of the first recognition process being based on context information rather than on express user instruction; launching the selected first recognition process, to discern information about a subject depicted in the captured imagery; receiving first data, after said selected first recognition process has been launched, said first data comprising (a) user input data indicating express or implied user encouragement or discouragement of said first recognition process by the user, and/or (b) a detection state metric, representing a quantified likelihood that a recognition goal sought by the first recognition process will be reached; and allocating increased or decreased resources to said first recognition process based on said received first data, said allocation of increased resources being apart from increased resource usage due to any increasing base complexity of successive stages of the selected first recognition process.
  16. The computer readable storage medium of claim 15 in which said instructions configure the system to allocate increased resources to said first recognition process based on user input data indicating express or implied user encouragement of said first recognition process by the user.
  17. The computer readable storage medium of claim 15 in which said instructions configure the system to allocate decreased resources to said first recognition process based on user input data indicating express or implied user discouragement of said first recognition process by the user.
  18. The computer readable storage medium of claim 15 in which said instructions configure the system to allocate increased resources to said first recognition process based on said detection state metric.
  19. The computer readable storage medium of claim 15 in which said instructions configure the system to allocate decreased resources to said first recognition process based on said detection state metric.
  20. A mobile system comprising a processor, memory and camera, the memory further comprising software instructions to configure the mobile system to perform acts including: selecting a first recognition process to apply to imagery captured by the camera, from among several recognition processes that the system is equipped to apply, said selection of the first recognition process being based on context information rather than on express user instruction; launching the selected first recognition process, to discern information about a subject depicted in the captured imagery; receiving first data, after said selected first recognition process has been launched, said first data comprising (a) user input data indicating express or implied user encouragement or discouragement of said first recognition process by the user, and/or (b) a detection state metric, representing a quantified likelihood that a recognition goal sought by the first recognition process will be reached; and allocating increased or decreased resources to said first recognition process based on said received first data, said allocation of increased resources being apart from increased resource usage due to any increasing base complexity of successive stages of the selected first recognition process.

Description

The present specification concerns a variety of technologies; most concern enabling smart phones and other mobile devices to respond to the user's environment, e.g., by serving as intuitive hearing and seeing devices.

Cell phones have evolved from single purpose communication tools, to multi-function computer platforms. “There's an ap for that” is a familiar refrain.

Over a hundred thousand applications are available for smart phones - offering an overwhelming variety of services. However, each of these services must be expressly identified and launched by the user.

This is a far cry from the vision of ubiquitous computing, dating back over twenty years, in which computers demand less of our attention, rather than more. A truly “smart” phone would be one that takes actions - autonomously - to fulfill inferred or anticipated user desires.

A leap forward in this direction would be to equip cell phones with technology making them intelligent seeing/hearing devices - monitoring the user's environment and automatically selecting and undertaking operations responsive to visual and/or other stimulus.

There are many challenges to realizing such a device. These include technologies for understanding what input stimulus to the device represents, for inferring user desires based on that understanding, and for interacting with the user in satisfying those desires. Perhaps the greatest of these is the first, which is essentially the long-standing problem of machine cognition.

Consider a cell phone camera. For each captured frame, it outputs a million or so numbers (pixel values).

Citations (118)

  • US20060247915A1
  • US6466232B1
  • US6400996B1
  • US6445460B1
  • US6947571B1
  • US7022075B2
  • US7016532B2
  • US20020102966A1
  • US20020113757A1
  • US6722569B2
  • US20030095681A1
  • US20040212630A1
  • US7020337B2
  • US7313759B2
  • US7616840B2
  • US20040263663A1
  • US20050091604A1
  • US20050125224A1
  • US20060240862A1
  • US7751805B2
  • US20060012677A1
  • US7565139B2
  • US20050185060A1
  • US20070159522A1
  • US20050261990A1
  • US20060013446A1
  • US20060031684A1
  • US20060032726A1
  • US20060230073A1
  • US20060268007A1
  • US20070002077A1
  • US20060047704A1
  • US20060218192A1
  • US20060047584A1
  • US20060067575A1
  • US20060092291A1
  • US7508954B2
  • US7797338B2
  • US20060217199A1
  • US7657100B2
  • US20080082426A1
  • US7542610B2
  • US7519200B2
  • US20070036469A1
  • US20090295942A1
  • WO2007021996A2
  • US8020770B2
  • US20070100480A1
  • US8385039B2
  • US20070162971A1
  • US20070162942A1
  • US7787697B2
  • US20080005091A1
  • US20110167053A1
  • US20080002914A1
  • US20080007620A1
  • US20080122796A1
  • US20080174570A1
  • US20080235570A1
  • US20080300011A1
  • US20090016645A1
  • US20080267504A1
  • US20100309226A1
  • US20080306924A1
  • US20090031381A1
  • JP2009088903A
  • US20090094289A1
  • US20090175499A1
  • US20090203355A1
  • US20090237546A1
  • US20090242620A1
  • US20090279794A1
  • US20090303231A1
  • US20090310814A1
  • US20090319388A1
  • US20090327272A1
  • US20100048242A1
  • US20100046842A1
  • US20110164064A1
  • US20110202466A1
  • US20100119208A1
  • US20100131443A1
  • US20100226526A1
  • US20100198870A1
  • US20100199232A1
  • US20100205628A1
  • US20100208997A1
  • US20100261465A1
  • US20110125735A1
  • US20110035406A1
  • US20110038512A1
  • US20110063317A1
  • US9609107B2
  • US20110098029A1
  • US20140323142A1
  • US8737986B2
  • US9234744B2
  • US20160379082A1
  • WO2011059761A1
  • US8175617B2
  • US8121618B2
  • US20110116690A1
  • US20110129153A1
  • US20110131235A1
  • US20110131241A1
  • US20110128288A1
  • US20110137895A1
  • US20110135207A1
  • US20110158558A1
  • US20110164163A1
  • US20110165896A1
  • US20110197226A1
  • US20110199479A1
  • US20130200999A1
  • US20110244919A1
  • US9256806B2
  • WO2011116309A1
  • US8700392B1
Record as JSON 
{
  "publication_number": "US9888105B2",
  "country": "US",
  "kind": "B2",
  "title": "Intuitive computing methods and systems",
  "abstract": "A smart phone senses audio, imagery, and/or other stimulus from a user's environment, and acts autonomously to fulfill inferred or anticipated user desires. In one aspect, the detailed technology concerns phone-based cognition of a scene viewed by the phone's camera. Recognition tasks, selected with the aid of context, are allocated increased or decreased resources based on data comprising (a) user input data indicating express or implied encouragement or discouragement of the recognition task and/or (b) a detection state metric, representing a quantified likelihood that the recognition goal sought by the recognition task will be reached. A great number of other features and arrangements are also detailed.",
  "claims": [
    "1. An image processing method comprising the acts: capturing imagery with a camera portion of a mobile system, the system also including a processor controlled by configuration instructions stored in a memory; selecting a first recognition process to apply to the captured imagery, from among several recognition processes that the system is equipped to apply, said selection of the first recognition process being based on context information rather than on express user instruction; launching the selected first recognition process, employing said processor, to discern information about a subject depicted in the captured imagery; receiving first data, after said selected first recognition process has been launched, said first data comprising (a) user input data indicating express or implied user encouragement or discouragement of said first recognition process by the user, and/or (b) a detection state metric, representing a quantified likelihood that a recognition goal sought by the first recognition process will be reached; and allocating increased or decreased resources to said first recognition process based on said received first data, said allocation of increased resources being apart from increased resource usage due to any increasing base complexity of successive stages of the selected first recognition process.",
    "2. The method of claim 1 in which the received first data comprises user input data indicating user encouragement of said process, and the method includes allocating increased resources to said first recognition process based on said indication of encouragement, wherein the mobile system seems to respond intuitively to a user interest in said subject.",
    "3. The method of claim 1 in which the received first data indicates comprises user input data indicating user discouragement of said process, and the method includes allocating reduced resources to said first recognition process based on said indication of discouragement, wherein the mobile system seems to respond intuitively to a user dis-interest in said subject.",
    "4. The method of claim 1 in which the received first data comprises a detection state metric representing a quantified likelihood that the recognition goal sought by the first recognition process will be reached, and the method includes allocating increased resources to the first recognition process as a consequence of said detection state metric.",
    "5. The method of claim 1 in which the received first data comprises a detection state metric representing a quantified likelihood that the recognition goal sought by the first recognition process will be reached, and the method includes allocating decreased resources to the first recognition process as a consequence of said detection state metric.",
    "6. The method of claim 1 that includes: receiving user data indicating express or implied user encouragement or discouragement of the first recognition process; and receiving a detection state metric representing a quantified likelihood that the recognition goal sought by the first recognition process will be reached; wherein the method includes allocating resources to said first recognition process based on both (1) said received user data; and (2) said received detection state metric.",
    "7. The method of claim 1 in which the context information on which selection of the first recognition process is based, comprises image information.",
    "8. The method of claim 7 that includes selecting said first recognition process, from the several recognition processes the system is equipped to apply, based on results of baseline image processing operations applied to the captured imagery.",
    "9. The method of claim 7 that includes selecting said first recognition process, from the several recognition processes the system is equipped to apply, also based on context data distinct from image data.",
    "10. The method of claim 7 in which the context information on which selection of the first recognition process is based, also comprises location information.",
    "11. The method of claim 1 in which the context information on which selection of the first recognition process is based, comprises location information.",
    "12. The method of claim 1 that includes selecting said first recognition process, from the several recognition processes the system is equipped to apply, based on context data distinct from image data.",
    "13. The method of claim 1 that includes: selecting both first and second recognition processes to apply to the captured imagery, from among said several recognition processes the system is equipped to apply, based on context information rather than on express user instruction; launching both the first and second recognition processes; receiving second data, after said second recognition process has been launched, said second data comprising (a) user input data indicating express or implied user encouragement or discouragement of said second recognition process by the user, and/or (b) a detection state metric, representing a quantified likelihood that a recognition goal sought by the second recognition process will be reached; and based on the received first and second data, allocating increased resources to the first recognition process, and allocating reduced resources to the second recognition process.",
    "14. The method of claim 1 in which allocating increased resources to said first recognition process comprises making GPU resources available instead of CPU resources, allocating more scratchpad memory for calculations, allowing access to faster-responding memory, allowing increased power consumption, or allowing access to a faster network connection.",
    "15. A non-transitory computer readable storage medium containing software instructions to configure a mobile system, equipped with a processor and a camera, to perform acts including: selecting a first recognition process to apply to imagery captured by the camera, from among several recognition processes that the system is equipped to apply, said selection of the first recognition process being based on context information rather than on express user instruction; launching the selected first recognition process, to discern information about a subject depicted in the captured imagery; receiving first data, after said selected first recognition process has been launched, said first data comprising (a) user input data indicating express or implied user encouragement or discouragement of said first recognition process by the user, and/or (b) a detection state metric, representing a quantified likelihood that a recognition goal sought by the first recognition process will be reached; and allocating increased or decreased resources to said first recognition process based on said received first data, said allocation of increased resources being apart from increased resource usage due to any increasing base complexity of successive stages of the selected first recognition process.",
    "16. The computer readable storage medium of claim 15 in which said instructions configure the system to allocate increased resources to said first recognition process based on user input data indicating express or implied user encouragement of said first recognition process by the user.",
    "17. The computer readable storage medium of claim 15 in which said instructions configure the system to allocate decreased resources to said first recognition process based on user input data indicating express or implied user discouragement of said first recognition process by the user.",
    "18. The computer readable storage medium of claim 15 in which said instructions configure the system to allocate increased resources to said first recognition process based on said detection state metric.",
    "19. The computer readable storage medium of claim 15 in which said instructions configure the system to allocate decreased resources to said first recognition process based on said detection state metric.",
    "20. A mobile system comprising a processor, memory and camera, the memory further comprising software instructions to configure the mobile system to perform acts including: selecting a first recognition process to apply to imagery captured by the camera, from among several recognition processes that the system is equipped to apply, said selection of the first recognition process being based on context information rather than on express user instruction; launching the selected first recognition process, to discern information about a subject depicted in the captured imagery; receiving first data, after said selected first recognition process has been launched, said first data comprising (a) user input data indicating express or implied user encouragement or discouragement of said first recognition process by the user, and/or (b) a detection state metric, representing a quantified likelihood that a recognition goal sought by the first recognition process will be reached; and allocating increased or decreased resources to said first recognition process based on said received first data, said allocation of increased resources being apart from increased resource usage due to any increasing base complexity of successive stages of the selected first recognition process."
  ],
  "description_excerpt": "The present specification concerns a variety of technologies; most concern enabling smart phones and other mobile devices to respond to the user's environment, e.g., by serving as intuitive hearing and seeing devices.\n\nCell phones have evolved from single purpose communication tools, to multi-function computer platforms. “There's an ap for that” is a familiar refrain.\n\nOver a hundred thousand applications are available for smart phones - offering an overwhelming variety of services. However, each of these services must be expressly identified and launched by the user.\n\nThis is a far cry from the vision of ubiquitous computing, dating back over twenty years, in which computers demand less of our attention, rather than more. A truly “smart” phone would be one that takes actions - autonomously - to fulfill inferred or anticipated user desires.\n\nA leap forward in this direction would be to equip cell phones with technology making them intelligent seeing/hearing devices - monitoring the user's environment and automatically selecting and undertaking operations responsive to visual and/or other stimulus.\n\nThere are many challenges to realizing such a device. These include technologies for understanding what input stimulus to the device represents, for inferring user desires based on that understanding, and for interacting with the user in satisfying those desires. Perhaps the greatest of these is the first, which is essentially the long-standing problem of machine cognition.\n\nConsider a cell phone camera. For each captured frame, it outputs a million or so numbers (pixel values).",
  "cpc": [
    "H04W 4/02",
    "G01C 21/00",
    "G01C 21/20",
    "G01C 21/36",
    "G06F 18/24",
    "G06F 3/005",
    "G06F 3/011",
    "G06F 3/017",
    "G06F 3/023",
    "G06F 3/04817",
    "G06F 3/0482",
    "G06F 3/04842",
    "G06F 3/04847",
    "G06F 3/04886",
    "G06K 9/00671",
    "G06K 9/62",
    "G06K 9/6267",
    "G06Q 10/10",
    "G06T 19/006",
    "G06T 2200/24",
    "G06V 20/20",
    "G09G 5/00",
    "H04M 1/724",
    "H04M 1/72403",
    "H04M 1/72519",
    "H04M 1/72522",
    "H04M 2250/22",
    "H04M 2250/74",
    "H04N 23/667",
    "H04N 23/80",
    "H04N 5/225",
    "H04N 5/23229",
    "H04N 5/23245",
    "H04W 4/024",
    "H04W 4/027",
    "H04W 4/029",
    "H04W 88/02"
  ],
  "ipc": [
    "G01C 21/20",
    "G01C 21/36",
    "H04M 1/724",
    "H04M 1/72403",
    "H04N 23/80",
    "G01C 21/00",
    "G06F 3/00",
    "G06F 3/01",
    "G06F 3/023",
    "G06F 3/0481",
    "G06F 3/0484",
    "G06F 3/0488",
    "G06K 9/62",
    "G06Q 10/10",
    "G06T 19/00",
    "G09G 5/00",
    "H04W 4/02"
  ],
  "assignees": [
    "Digimarc Corp"
  ],
  "inventors": [
    "Geoffrey B. Rhoads"
  ],
  "filing_date": "2017-03-23",
  "publication_date": "2018-02-06",
  "grant_date": "2018-02-06",
  "priority_date": "2009-10-28",
  "application_number": "US-201715467819-A",
  "family_id": "44507193",
  "cited_by_count": 19,
  "citations": [
    "US20060247915A1",
    "US6466232B1",
    "US6400996B1",
    "US6445460B1",
    "US6947571B1",
    "US7022075B2",
    "US7016532B2",
    "US20020102966A1",
    "US20020113757A1",
    "US6722569B2",
    "US20030095681A1",
    "US20040212630A1",
    "US7020337B2",
    "US7313759B2",
    "US7616840B2",
    "US20040263663A1",
    "US20050091604A1",
    "US20050125224A1",
    "US20060240862A1",
    "US7751805B2",
    "US20060012677A1",
    "US7565139B2",
    "US20050185060A1",
    "US20070159522A1",
    "US20050261990A1",
    "US20060013446A1",
    "US20060031684A1",
    "US20060032726A1",
    "US20060230073A1",
    "US20060268007A1",
    "US20070002077A1",
    "US20060047704A1",
    "US20060218192A1",
    "US20060047584A1",
    "US20060067575A1",
    "US20060092291A1",
    "US7508954B2",
    "US7797338B2",
    "US20060217199A1",
    "US7657100B2",
    "US20080082426A1",
    "US7542610B2",
    "US7519200B2",
    "US20070036469A1",
    "US20090295942A1",
    "WO2007021996A2",
    "US8020770B2",
    "US20070100480A1",
    "US8385039B2",
    "US20070162971A1",
    "US20070162942A1",
    "US7787697B2",
    "US20080005091A1",
    "US20110167053A1",
    "US20080002914A1",
    "US20080007620A1",
    "US20080122796A1",
    "US20080174570A1",
    "US20080235570A1",
    "US20080300011A1",
    "US20090016645A1",
    "US20080267504A1",
    "US20100309226A1",
    "US20080306924A1",
    "US20090031381A1",
    "JP2009088903A",
    "US20090094289A1",
    "US20090175499A1",
    "US20090203355A1",
    "US20090237546A1",
    "US20090242620A1",
    "US20090279794A1",
    "US20090303231A1",
    "US20090310814A1",
    "US20090319388A1",
    "US20090327272A1",
    "US20100048242A1",
    "US20100046842A1",
    "US20110164064A1",
    "US20110202466A1",
    "US20100119208A1",
    "US20100131443A1",
    "US20100226526A1",
    "US20100198870A1",
    "US20100199232A1",
    "US20100205628A1",
    "US20100208997A1",
    "US20100261465A1",
    "US20110125735A1",
    "US20110035406A1",
    "US20110038512A1",
    "US20110063317A1",
    "US9609107B2",
    "US20110098029A1",
    "US20140323142A1",
    "US8737986B2",
    "US9234744B2",
    "US20160379082A1",
    "WO2011059761A1",
    "US8175617B2",
    "US8121618B2",
    "US20110116690A1",
    "US20110129153A1",
    "US20110131235A1",
    "US20110131241A1",
    "US20110128288A1",
    "US20110137895A1",
    "US20110135207A1",
    "US20110158558A1",
    "US20110164163A1",
    "US20110165896A1",
    "US20110197226A1",
    "US20110199479A1",
    "US20130200999A1",
    "US20110244919A1",
    "US9256806B2",
    "WO2011116309A1",
    "US8700392B1"
  ]
}

Record 3,598 of 8,000 in Patents full text (MLC-0201). Request the full dataset.