# US 10,121,092 B2 · Metric-based recognition, systems and methods > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 10,121,092 B2 - Document ID: US10121092B2 - Status: Granted - Kind: B2 - Application number: 15/785,932 - Filed: 2017-10-17 - Published: 2018-02-08 - Granted: 2018-11-06 - Earliest claimed: 2013-08-19 - Assignees: Nant Holdings IP, LLC - Applicants: Nant Holdings IP, LLC - Inventors: Matheen Siddiqui - Web page: https://patentgrep.com/patent/US10121092B2 ## CPC - G06F 16/5838: {using colour} - G06F 16/3331: Query processing - G06F 16/51: Indexing; Data structures therefor; Storage structures - G06F 16/7335: {Graphical querying, e.g. query-by-region, query-by-sketch, query-by-trajectory, GUIs for designating a person/face/object as a query predicate (end-user interface involving hot spots associated with the video H04N21/4725; end-user interface for selecting a Region of Interest H04N21/4728)} - G06F 16/785: {using colour or luminescence} - G06F 16/907: Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually - G06V 10/56: relating to colour - G06V 30/422: Technical drawings; Geographical maps - H04N 1/40012: {Conversion of colour to monochrome} - G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N) - G06V: IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING - H04N: PICTORIAL COMMUNICATION, e.g. TELEVISION ## Abstract Apparatus, methods and systems of object recognition are disclosed. Embodiments of the inventive subject matter generates map-altered image data according to an object-specific metric map, derives a metric-based descriptor set by executing an image analysis algorithm on the map-altered image data, and retrieves digital content associated with a target object as a function of the metric-based descriptor set. ## Claims ### Claim 1 A method of generating a metric-based recognition map comprising: receiving, by a computing device configured to operate as an image processing engine, image data; compiling, by the image processing engine, an initial object-specific metric map for a specific human person from at least a portion of the image data where the portion represents at least a portion of the object; generating, by the image processing engine, a metric-based descriptor set by executing an image analysis algorithm on the portion of the image data as a function of the initial object-specific metric map; and storing the metric-based descriptor set in an object recognition database. ### Claim 2 (depends on 1) The method of claim 1, further comprising adjusting the initial object-specific metric map to generate a new object-specific metric map by tuning metric values in a manner effective to enhance differentiation of descriptors generated by the image analysis algorithm as executed on the portion of the image data. ### Claim 3 (depends on 2) The method of claim 2, wherein adjusting the initial object-specific metric map includes accepting user input that alters at least some metric values within the initial object-specific metric map. ### Claim 4 (depends on 2) The method of claim 2, wherein adjusting the initial object-specific metric map includes the image processing engine recommending at least one a metric value that increases a confidence of a descriptor. ### Claim 5 (depends on 2) The method of claim 2, wherein adjusting the initial object-specific metric map includes the image processing engine automatically adjusting metric values of the initial object-specific metric map. ### Claim 6 (depends on 2) The method of claim 2, wherein the new metric-based map comprises a non-linear mapping from metric values within the initial metric-based map. ### Claim 7 (depends on 1) The method of claim 1, further comprising generating an object-specific color map based the object-specific metric map. ### Claim 8 (depends on 7) The method of claim 7, further comprising storing the object-specific color map as part of the metric-based descriptor set. ### Claim 9 (depends on 1) The method of claim 1, further comprising identifying at least one of a position and an orientation of an imaging device configured to capture the image data. ### Claim 10 (depends on 9) The method of claim 9, further comprising storing the at least one of the position and the orientation with the metric-based descriptor set. ### Claim 11 (depends on 1) The method of claim 1, further comprising removing specularity from the image data. ### Claim 12 (depends on 1) The method of claim 1, wherein the object-specific metric map comprises a pixel-level metric map. ### Claim 13 (depends on 1) The method of claim 1, wherein the metric-based descriptor set comprises lighting invariant descriptors. ### Claim 14 (depends on 1) The method of claim 1, wherein the metric-based descriptor set comprises metric-based invariant descriptors. ### Claim 15 (depends on 14) The method of claim 14, wherein the metric-based descriptors comprise metric-based scale invariant descriptors. ### Claim 16 (depends on 1) The method of claim 1, wherein the object comprises a physical object. ### Claim 17 (depends on 1) The method of claim 1, further comprising storing a key frame bundle that includes the metric-based descriptor set. ### Claim 18 (depends on 1) The method of claim 1, wherein the map is focused on skin tone. ### Claim 19 (depends on 1) The method of claim 1, wherein the map comprises a tissue-specific map. ### Claim 20 (depends on 18) The method of claim 18, further comprising identifying skin tone variations of a specific person's face that are indicative of a skin lesion or other abnormality. ### Claim 21 (depends on 19) The method of claim 19, further comprising one or more tissue-specific maps that aid in differentiating structure or features of internal organs during surgery. ### Claim 22 (depends on 21) The method of claim 21, wherein one or more features such as tumors are identified because such features fail to conform to the person's tissue-specific maps. ### Claim 23 A non-transitory computer readable medium storing instructions executable on a processor for processing image data to generate a metric-based recognition map, the instructions comprising instructions to: compile an initial object-specific metric map for a specific human person from at least a portion of the image data where the portion represents at least a portion of the object; generate a metric-based descriptor set by executing an image analysis algorithm on the portion of the image data as a function of the initial object-specific metric map; and store the metric-based descriptor set in an object recognition database. ### Claim 24 A device for generating a metric-based recognition map comprising: a computing device configured to operate as an image processing engine, the image processing engine configured to: receive image data; compile an initial object-specific metric map for a specific human person from at least a portion of the image data where the portion represents at least a portion of the object; generate a metric-based descriptor set by executing an image analysis algorithm on the portion of the image data as a function of the initial object-specific metric map; and store the metric-based descriptor set in an object recognition database.