Object Detection for Video Camera Self-Calibration

• US 20180189532A1
• Filed: 12/30/2016
• Published: 07/05/2018
• Est. Priority Date: 12/30/2016
• Status: Active Grant

• Current Assignee: Accenture Global Solutions Limited (Accenture PLC)
• Original Assignee: Accenture Global Solutions Limited (Accenture PLC)
• Granted Patent: US 10,366,263 B2
• Time in Patent Office: Days
• CPC Class Codes: G06F 18/24 Classification techniques
• CPC Class Codes: G06K 19/06037 multi-dimensional coding
• CPC Class Codes: G06K 7/10811 Focalisation
• CPC Class Codes: G06K 7/1417 2D bar codes
• CPC Class Codes: G06K 7/1443 locating of the code in an image
• CPC Class Codes: G06T 2207/10024 Color image
• CPC Class Codes: G06T 2207/30204 Marker
• CPC Class Codes: G06T 7/80 Analysis of captured images to determine intrinsic or extrinsic camera parameters, i.e. camera calibration
• CPC Class Codes: G06V 10/245 by locating a pattern; Special marks for positioning
• CPC Class Codes: G06V 10/56 relating to colour
• CPC Class Codes: G06V 20/20 in augmented reality scenes
• CPC Class Codes: G06V 20/52 Surveillance or monitoring of activities, e.g. for recognising suspicious objects recognising microscopic objects G06V20/69

Abstract

This document describes systems, methods, devices, and other techniques for video camera self-calibration based on video information received from the video camera. In some implementations, a computing device receives video information characterizing a video showing a scene from a field of view of a video camera; detects an object that appears in the scene of the video; identifies a visual marking that appears on the detected object; determines a particular visual marking among a plurality of pre-defined visual markings that matches the visual marking that appears on the detected object; identifies one or more object characteristics associated with the particular visual marking; evaluates one or more features of the video with respect to the one or more object characteristics; and based on a result of evaluating the one or more features of the video with respect to the one or more object characteristics, sets a parameter of the video camera.

Claims

1. A computer-implemented method, comprising:

receiving, by a computing system, video information that characterizes a video showing a scene from a field of view of a video camera;

detecting, by the computing system and based on analysis of the video information, an object that appears in the scene of the video;

identifying, by the computing system, a visual marking that appears on the detected object;

determining, by the computing system, a particular visual marking, among a plurality of pre-defined visual markings available to the computing system, that matches the visual marking that appears on the detected object;

identifying, based on stored data that correlates the plurality of pre-defined visual markings with characteristics of respective objects on which the pre-defined visual markings can appear, one or more real world object characteristics that are defined for objects having the particular visual marking that appears on the detected object;

evaluating one or more features of the video with respect to the one or more real world object characteristics including comparing one or more characteristics of the detected object as they appear in the video to respective ones of the one or more real world object characteristics that are defined for objects having the particular visual marking that appears on the detected object;

based on a result of evaluating the one or more features of the video with respect to the one or more real world object characteristics selecting a setting for an operational parameter of the video camera, and

setting the operational parameter of the video camera according to the selected setting.

2. The method of claim 1, wherein the visual marking comprises a quick-response (QR) code.

3. The method of claim 1, wherein the visual marking comprises an encoded pattern printed on the detected object that uniquely identifies the detected object.

4. The method of claim 1, wherein each of the plurality of pre-defined visual markings identify a unique set of real world object characteristics.

5. The method of claim 4, wherein the unique set of real world object characteristics comprise one or more of (i) real-world dimensions of the object and (ii) real-world location of the object.

6. The method of claim 5, wherein evaluating one or more features of the video with respect to the one or more real world object characteristics comprises comparing dimensions of the object as they appear in the video to the real-world dimensions of the object to determine a distance of the camera from the object.

7. The method of claim 6, wherein selecting a setting for an operational parameter of the video camera comprises selecting a setting for the focal length of the video camera, and wherein setting the operational parameter of the video camera according to the selected setting comprises setting the focal length of the video camera based on the determined distance.

8. The method of claim 6, wherein selecting a setting for an operational parameter of the video camera comprises selecting the geographic location of the video camera, and wherein setting the operational parameter of the video camera according to the selected setting comprises storing a geographic location of the video camera based on the determined distance and real-world location of the object.

9. The method of claim 4, wherein the visual marking comprises one or more colours, and

wherein the unique set of real world object characteristics that are defined for objects having the visual marking identifies the one or more colours of the visual marking.

10. The method of claim 9, wherein evaluating one or more features of the video with respect to the one or more real world object characteristics comprises comparing a colorization of the visual marking as it appears in the video to the one or more colours indicated by the unique set of real world object characteristics that are defined for objects having the visual marking.

11. The method of claim 10, wherein selecting a setting for an operational parameter of the video camera comprises selecting a color setting of the video camera, and wherein setting the operational parameter of the video camera comprises adjusting a colour setting of the video camera.

12. The method of claim 4, wherein the unique set of real world object characteristics indicate that the object is located on a ground plane.

13. The method of claim 12, wherein selecting a setting for an operational parameter of the video camera comprises selecting an orientation of the video camera, and wherein setting the operational parameter of the video camera comprises determining an orientation of the camera relative to the ground plane.

14. The method of claim 4, wherein the unique set of real world object characteristics comprise a height of the object above the ground plane, and wherein evaluating one or more features of the video with respect to the one or more real world object characteristics comprises modeling the ground plane of the scene.

16. The method of claim 1, wherein the detected object comprises a rotakin.

17. The method of claim 1, wherein (i) the detected object comprises a card, and (ii) the visual marking that appears on the detected object comprises a glyph printed on the card.

18. The method of claim 1, wherein identifying one or more real world object characteristics that are defined for objects having the particular visual marking that appears on the detected object comprises querying a remotely stored database.

21. The method of claim 1, wherein evaluating one or more features of the video with respect to the one or more real world object characteristics comprises determining a spatial relationship between the video camera and the detected object, and wherein selecting a setting for an operational parameter of the video camera comprises selecting a setting for an operational parameter based on the determined spatial relationship between the video camera and the detected object.

15. (canceled)

19. A system comprising:

one or more processors; and

one or more computer-readable media having instructions stored thereon which, when executed by the one or more processors, cause the one or more processors to perform operations comprising;

receiving video information that characterizes a video showing a scene from a field of view of a video camera;

detecting, based on analysis of the video information, an object that appears in the scene of the video;

identifying a visual marking that appears on the detected object;

determining a particular visual marking, among a plurality of pre-defined visual markings available to the computing system, that matches the visual marking that appears on the detected object;

identifying, based on stored data that correlates the plurality of pre-defined visual markings with characteristics of respective objects on which the pre-defined visual markings can appear, one or more real world object characteristics that are defined for objects having the particular visual marking that appears on the detected object;

evaluating one or more features of the video with respect to the one or more real world object characteristics including comparing one or more characteristics of the detected object as they appear in the video to respective ones of the one or more real world object characteristics that are defined for objects having the particular visual marking that appears on the detected object;

based on a result of evaluating the one or more features of the video with respect to the one or more real world object characteristics selecting a setting for an operational parameter of the video camera, and setting the operational parameter of the video camera according to the selected setting.

20. A computer-implemented method, comprising:

receiving, by a computing system, video information that characterizes a video showing a scene from a field of view of a video camera;

detecting, by the computing system and based on analysis of the video information, an object that appears in the scene of the video;

applying, by the computing system, a bounding box in the field of view around the detected object;

classifying, by the computing system, the detected object as a particular object;

determining, based on stored data that correlates objects with respective object characteristics, one or more properties of the bounding box in the field of view around the detected object;

evaluating one or more features of the video with respect to the one or more properties of the bounding box in the field of view around the detected object;

based on a result of evaluating the one or more features of the video with respect to the one or more properties of the bounding box in the field of view around the detected object, selecting a setting for an operational parameter of the video camera; and

setting a-the operational parameter of the video camera according to the selected setting.