Image capture and identification system and process

• US 10,617,568 B2
• Filed: 08/29/2018
• Issued: 04/14/2020
• Est. Priority Date: 11/06/2000
• Status: Expired due to Term

• Current Assignee: Nant Holdings IP, LLC (NantWorks, LLC)
• Original Assignee: Nant Holdings IP, LLC (NantWorks, LLC)
• Inventors: Boncyk, Wayne C., Cohen, Ronald H.
• Primary Examiner(s): Sherali, Ishrat I
• Application Number:
  US16/116,660
• Publication Number:
  US 20190008684A1
• Time in Patent Office: 594 Days
• Field of Search: 382103, 382104, 382305
• CPC Class Codes: A61F 9/08 Devices or methods enabling eye-patients to replace direct visual perception by another kind of perception
• CPC Class Codes: A63F 13/00 Video games, i.e. games using an electronically generated display having two or more dimensions gaming systems which provide a financial reward G07F17/32
• CPC Class Codes: A63F 13/20 Input arrangements for video game devices
• CPC Class Codes: A63F 13/213 comprising photodetecting means, e.g. cameras, photodiodes or infrared cells A63F13/219, A63F13/655 take precedence
• CPC Class Codes: A63F 13/335 using Internet
• CPC Class Codes: A63F 13/35 Details of game servers
• CPC Class Codes: A63F 13/45 Controlling the progress of the video game
• CPC Class Codes: A63F 13/65 automatically by game devices or servers from real world data, e.g. measurement in live racing competition
• CPC Class Codes: A63F 13/655 by importing photos, e.g. of the player
• CPC Class Codes: A63F 13/70 Game security or game management aspects
• CPC Class Codes: A63F 13/792 for payment purposes, e.g. monthly subscriptions
• CPC Class Codes: A63F 13/92 Video game devices specially adapted to be hand-held while playing
• CPC Class Codes: G06F 16/24 Querying
• CPC Class Codes: G06F 16/29 Geographical information databases
• CPC Class Codes: G06F 16/50 of still image data
• CPC Class Codes: G06F 16/51 Indexing; Data structures therefor; Storage structures
• CPC Class Codes: G06F 16/583 using metadata automatically derived from the content
• CPC Class Codes: G06F 16/5838 using colour
• CPC Class Codes: G06F 16/5846 using extracted text
• CPC Class Codes: G06F 16/5854 using shape and object relationship
• CPC Class Codes: G06F 16/5866 : using information manually generated, e.g. tags, keywords, comments, manually generated location and time information
• CPC Class Codes: G06F 16/94 : Hypermedia Hyperlinking G06F40/134
• CPC Class Codes: G06F 16/9554 : by using bar codes
• CPC Class Codes: G06F 16/9558 : Details of hyperlinks; Management of linked annotations
• CPC Class Codes: G06F 18/217 : Validation; Performance evaluation; Active pattern learning techniques
• CPC Class Codes: G06F 18/22 : Matching criteria, e.g. proximity measures
• CPC Class Codes: G06F 18/23 : Clustering techniques
• CPC Class Codes: G06F 18/254 : of classification results, e.g. of results related to same input data
• CPC Class Codes: G06F 2218/12 : Classification; Matching
• CPC Class Codes: G06F 3/0482 : Interaction with lists of selectable items, e.g. menus
• CPC Class Codes: G06F 40/134 : Hyperlinking
• CPC Class Codes: G06Q 10/02 : Reservations, e.g. for tickets, services or events
• CPC Class Codes: G06Q 20/102 : Bill distribution or payments
• CPC Class Codes: G06Q 20/14 : specially adapted for billing systems
• CPC Class Codes: G06Q 20/202 : Interconnection or interaction of plural electronic cash registers [ECR] or to host computer, e.g. network details, transfer of information from host to ECR or from ECR to ECR
• CPC Class Codes: G06Q 20/208 : Input by product or record sensing, e.g. weighing or scanner processing
• CPC Class Codes: G06Q 20/24 : Credit schemes, i.e. "pay after"
• CPC Class Codes: G06Q 20/327 : Short range or proximity payments by means of M-devices
• CPC Class Codes: G06Q 20/3567 : Software being in the reader
• CPC Class Codes: G06Q 20/40145 : Biometric identity checks
• CPC Class Codes: G06Q 30/0217 : involving input on products or services in exchange for incentives or rewards
• CPC Class Codes: G06Q 30/0241 : Advertisements
• CPC Class Codes: G06Q 30/0253 : During e-commerce, i.e. online transactions
• CPC Class Codes: G06Q 30/0257 : User requested
• CPC Class Codes: G06Q 30/0267 : Wireless devices
• CPC Class Codes: G06Q 30/0268 : at point-of-sale [POS]
• CPC Class Codes: G06Q 30/0269 : based on user profile or attribute
• CPC Class Codes: G06Q 30/0277 : Online advertisement
• CPC Class Codes: G06Q 30/04 : Billing or invoicing
• CPC Class Codes: G06Q 30/0601 : Electronic shopping [e-shopping]
• CPC Class Codes: G06Q 30/0623 : Item investigation
• CPC Class Codes: G06Q 30/0635 : Processing of requisition or of purchase orders
• CPC Class Codes: G06Q 30/0643 : Graphical representation of items or shoppers
• CPC Class Codes: G06Q 40/00 : Finance; Insurance; Tax strategies; Processing of corporate or income taxes
• CPC Class Codes: G06Q 90/00 : Systems or methods specially adapted for administrative, commercial, financial, managerial or supervisory purposes, not involving significant data processing
• CPC Class Codes: G06T 7/10 : Segmentation; Edge detection motion-based segmentation G06T7/215
• CPC Class Codes: G06T 7/11 : Region-based segmentation
• CPC Class Codes: G06T 7/13 : Edge detection
• CPC Class Codes: G06T 7/136 : involving thresholding
• CPC Class Codes: G06T 7/194 : involving foreground-background segmentation
• CPC Class Codes: G06T 7/246 : using feature-based methods, e.g. the tracking of corners or segments
• CPC Class Codes: G06T 7/33 : using feature-based methods
• CPC Class Codes: G06T 7/337 : involving reference images or patches
• CPC Class Codes: G06T 7/73 : using feature-based methods
• CPC Class Codes: G06V 10/462 : Salient features, e.g. scale invariant feature transforms [SIFT]
• CPC Class Codes: G06V 10/56 : relating to colour
• CPC Class Codes: G06V 10/7515 : Shifting the patterns to accommodate for positional errors
• CPC Class Codes: G06V 20/10 : Terrestrial scenes scenes under surveillance with static cameras G06V20/52; scenes perceived from the exterior of a vehicle G06V20/56; scenes perceived from the interior of a vehicle G06V20/59
• CPC Class Codes: G06V 20/20 : in augmented reality scenes
• CPC Class Codes: G06V 30/142 : using hand-held instruments; Constructional details of the instruments
• CPC Class Codes: G06V 30/224 : of printed characters having additional code marks or containing code marks
• CPC Class Codes: G07F 17/3206 : Player sensing means, e.g. presence detection, biometrics
• CPC Class Codes: G07F 17/3241 : Security aspects of a gaming system, e.g. detecting cheating, device integrity, surveillance computer security G06F21/00
• CPC Class Codes: G07F 17/3244 : Payment aspects of a gaming system, e.g. payment schemes, setting payout ratio, bonus or consolation prizes
• CPC Class Codes: G09B 21/006 : using audible presentation of the information
• CPC Class Codes: H04L 67/02 : based on web technology, e.g. hypertext transfer protocol [HTTP]
• CPC Class Codes: H04L 67/10 : in which an application is distributed across nodes in the network software deployment G06F8/60; multiprogramming arrangements G06F9/46
• CPC Class Codes: H04N 1/00244 : with a server, e.g. an internet server fax-servers or the like for store and forward H04N1/324
• CPC Class Codes: H04N 21/23109 : by placing content in organized collections, e.g. EPG data repository details of retrieval of video data and associated meta data in video databases G06F16/739
• CPC Class Codes: H04N 21/23418 : involving operations for analysing video streams, e.g. detecting features or characteristics television picture signal circuitry for scene change detection H04N5/147; filtering for image enhancement G06T5/00; methods or arrangements for recognising scenes G06V20/00; arrangements characterised by components specially adapted for monitoring, identification or recognition of video in broadcast systems H04H60/59
• CPC Class Codes: H04N 21/254 : Management at additional data server, e.g. shopping server, rights management server arrangements for maintenance or administration in data networks H04L41/00; network services using third party service providers H04L67/53
• CPC Class Codes: H04N 21/41407 : embedded in a portable device, e.g. video client on a mobile phone, PDA, laptop constructional details of equipment or arrangements specially adapted for portable computer application G06F1/1626; arrangements specially adapted for mobile receivers in broadcast systems H04H20/57
• CPC Class Codes: H04N 21/4223 : Cameras H04N23/00 takes precedence
• CPC Class Codes: H04N 21/44224 : Monitoring of user activity on external systems, e.g. Internet browsing
• CPC Class Codes: H04N 21/4722 : for requesting additional data associated with the content
• CPC Class Codes: H04N 21/4781 : Games
• CPC Class Codes: H04N 21/47815 : Electronic shopping payment schemes, payment architectures or payment protocols for electronic shopping systems G06Q20/12
• CPC Class Codes: H04N 21/4782 : Web browsing , e.g. WebTV
• CPC Class Codes: H04N 21/6582 : Data stored in the client, e.g. viewing habits, hardware capabilities, credit card number arrangements where receivers interact with the broadcast H04H20/38
• CPC Class Codes: H04N 21/812 : involving advertisement data advertising per se G06Q30/02
• CPC Class Codes: H04N 21/8126 : involving additional data, e.g. news, sports, stocks, weather forecasts
• CPC Class Codes: H04N 21/8173 : End-user applications, e.g. Web browser, game
• CPC Class Codes: H04N 2201/3253 : Position information, e.g. geographical position at time of capture, GPS data
• CPC Class Codes: H04N 2201/3254 : Orientation, e.g. landscape or portrait; Location or order of the image data, e.g. in memory
• CPC Class Codes: H04N 2201/3274 : Storage or retrieval of prestored additional information
• CPC Class Codes: H04N 23/00 : Cameras or camera modules comprising electronic image sensors; Control thereof
• CPC Class Codes: H04N 23/64 : Computer-aided capture of images, e.g. transfer from script file into camera, check of taken image quality, advice or proposal for image composition or decision on when to take image
• CPC Class Codes: H04N 23/661 : Transmitting camera control signals through networks, e.g. control via the Internet
• CPC Class Codes: H04N 23/80 : Camera processing pipelines; Components thereof
• CPC Class Codes: H04N 5/91 : Television signal processing therefor
• CPC Class Codes: H04N 7/183 : for receiving images from a single remote source
• CPC Class Codes: H04N 7/185 : from a mobile camera, e.g. for remote control

Abstract

A digital image depicting a digital representation of a scene is captured by an image sensor of a vehicle. An identification system recognizes a real-world object from the digital image as a target object based on derived image characteristics and identifies object information about the target object based on the recognition. The identification provides the object information to the vehicle data system of the vehicle so that the vehicle data system can execute a control function of the vehicle based on the received object information.

Claims

1. A method for vehicle-based object recognition, comprising:

obtaining, by at least one first processor, image data captured by an image sensor of a vehicle, the image data containing a digital representation of a real-world object within a scene;

deriving, by the at least one first processor, image characteristics of the real-world object from the digital representation of the real-world object in the image data, wherein the image characteristics comprise salient parameters;

recognizing, by the at least one first processor, the real-world object as a target object based on the derived image characteristics;

identifying, by the at least one first processor, object information about the target object based on the recognition;

providing, by the at least one first processor and to at least one second processor of the vehicle, the object information; and

executing, by the at least one second processor, a control function of the vehicle based on the object information.

2. The method of claim 1, wherein the control function comprises at least one of guidance, navigation or maneuvering of the vehicle relative to the real-world object.

3. The method of claim 1, wherein the control function comprises planning, by the vehicle data system, a trajectory relative to the real-world object.

4. The method of claim 1, wherein the object information comprises at least one of location or orientation of the real-world object relative to the vehicle.

5. The method of claim 1, wherein the real-world object is a street sign.

6. The method of claim 1, wherein the real-world object is another vehicle.

7. The method of claim 6, further comprising initiating, by the vehicle data system, a wireless communication with a computer system integral to the real-world object.

8. The method of claim 1, further comprising:

obtaining, by the at least one first processor, additional image data captured by an image sensor of at least one second vehicle, the additional image data containing an additional digital representation of the real-world object; and

wherein the method steps of deriving and recognizing are based on the image data and the additional image data.

9. The method of claim 1, further comprising initiating, by the at least one second processor, a process on a computer system remote to the vehicle.

10. The method of claim 1, wherein the at least one first processor is integral to the vehicle.

11. The method of claim 1, wherein the at least one first processor is remote from the vehicle.

12. The method of claim 1, further comprising:

obtaining, by the at least one second processor, location data corresponding to the location of the vehicle;

providing, by the at least one second processor to the at least one first processor, the location data; and

wherein the identifying step comprises identifying, by the at least one first processor, the object information about the target object based on the recognition and the location data.

13. The method of claim 1, wherein the vehicle comprises an autonomous vehicle.

14. A system comprising:

at least one first processor programmed to;

obtain image data captured by an image sensor of a vehicle, the image data containing a digital representation of a real-world object within a scene;

derive image characteristics of the real-world object from the digital representation of the real-world object in the image data, wherein the image characteristics comprise salient parameters;

recognize the real-world object as a target object based on the derived image characteristics;

identify object information about the target object based on the recognition; and

provide the object information to at least one second processor of the vehicle to enable the at least one second processor to execute the control function of the vehicle based on the object information.

15. The system of claim 14, further comprising the at least one second processor programmed to execute the control function, wherein the control function comprises at least one of guidance, navigation or maneuvering of the vehicle relative to the real-world object.

16. The system of claim 14, further comprising the at least one second processor programmed to execute the control function, wherein the executing of the control function comprises planning a trajectory relative to the real-world object.

17. The system of claim 14, wherein the object information comprises at least one of location or orientation of the real-world object relative to the vehicle.

18. The system of claim 14, wherein the real-world object is a street sign.

19. The system of claim 14, wherein the real-world object is another vehicle.

20. The system of claim 19, further comprising the at least one second processor programmed to initiate a wireless communication with a computer system integral to the real-world object.

21. The system of claim 14, wherein:

the at least one first processor is programmed to obtain additional image data captured by an image sensor of at least one second vehicle, the additional image data containing an additional digital representation of the real-world object; and

wherein the at least one first processor is programmed to derive and recognize based on the image data and the additional image data.

22. The system of claim 14, further comprising the at least second processor programmed to initiate a process on a computer system remote to the vehicle.

23. The system of claim 14, wherein the at least one first processor is integral to the vehicle.

24. The system of claim 14, wherein the at least one first processor is remote from the vehicle.

25. The system of claim 14, further comprising:

the at least one second processor programmed to obtain location data corresponding to the location of the vehicle; and

the at least one first processor programmed to identify comprises;

the at least one first processor programmed to identify the object information about the target object based on the recognition and the location data.

26. The system of claim 14, wherein the vehicle comprises an autonomous vehicle.

27. At least one non-transitory computer-readable storage medium storing instructions that, when executed by at least one processor, cause the at least one processor to:

obtain image data captured by an image sensor of a vehicle, the image data containing a digital representation of a real-world object within a scene;

derive image characteristics of the real-world object from the digital representation of the real-world object in the image data, wherein the image characteristics comprise salient parameters;

recognize the real-world object as a target object based on the derived image characteristics;

identify object information about the target object based on the recognition; and

execute a control function of the vehicle based on the object information.

28. The at least one non-transitory computer-readable storage medium of claim 27, wherein the control function comprises at least one of guidance, navigation or maneuvering of the vehicle relative to the real-world object.

29. The at least one non-transitory computer-readable storage medium of claim 27, wherein the executing of the control function comprises planning a trajectory relative to the real-world object.

30. The at least one non-transitory computer-readable storage medium of claim 27, wherein the object information comprises at least one of location or orientation of the real-world object relative to the vehicle.

31. The at least one non-transitory computer-readable storage medium of claim 27, wherein the real-world object is a street sign.

32. The at least one non-transitory computer-readable storage medium of claim 27, wherein the real-world object is another vehicle.

33. The at least one non-transitory computer-readable storage medium of claim 32, further storing instructions that, when executed by the at least one processor, further cause the at least one processor to initiate a wireless communication with a computer system integral to the real-world object.

34. The at least one non-transitory computer-readable storage medium of claim 27, further storing instructions that, when executed by the at least one processor, further cause the at least one processor to:

obtain additional image data captured by an image sensor of at least one second vehicle, the additional image data containing an additional digital representation of the real-world object; and

execute the derive and recognize instruction steps based on the image data and the additional image data.

35. The at least one non-transitory computer-readable storage medium of claim 27, further storing instructions that, when executed by the at least one processor, further cause the at least one processor to initiate a process on a computer system remote to the vehicle.

36. The at least one non-transitory computer-readable storage medium of claim 27, wherein the identification system is integral to the vehicle.

37. The at least one non-transitory computer-readable storage medium of claim 27, wherein the identification system is remote from the vehicle.

38. The at least one non-transitory computer-readable storage medium of claim 27, further storing instructions that, when executed by the at least one processor, further cause the at least one processor to:

obtain location data corresponding to the location of the vehicle; and

wherein the identify instruction step comprises instructions that, when executed by the at least one processor, cause the at least one processor to identify the object information about the target object based on the recognition and the location data.

39. The at least one non-transitory computer-readable storage medium of claim 27, wherein the vehicle comprises an autonomous vehicle.