CAMERA CALIBRATION APPLICATION

• US 20130342706A1
• Filed: 06/20/2012
• Published: 12/26/2013
• Est. Priority Date: 06/20/2012
• Status: Active Grant

• Current Assignee: Conduent Business Services, LLC (Conduent, Inc.)
• Original Assignee: Xerox Corporation (Xerox Holdings Corp.)
• Inventors: Hoover, Martin Edward, Wu, Wencheng, Kozitsky, Vladimir, Jackson, David Martin Todd
• Granted Patent: US 9,870,704 B2
• Time in Patent Office: Days
• US Class Current: 348/187
• CPC Class Codes: G06T 2207/10016 Video; Image sequence
• CPC Class Codes: G06T 2207/30204 Marker
• CPC Class Codes: G06T 2207/30236 Traffic on road, railway or crossing
• CPC Class Codes: G06T 7/80 Analysis of captured images to determine intrinsic or extrinsic camera parameters, i.e. camera calibration
• CPC Class Codes: G08G 1/0175 by photographing vehicles, e.g. when violating traffic rules
• CPC Class Codes: H04N 17/002 for television cameras

Abstract

A method and system for camera calibration comprises configuring a calibration target comprising calibration reflectors on a test vehicle. Video of a test scene is collected. Next the test vehicle is identified as it enters the test scene and recorded as it passes through the test scene. The position of the calibration target in each frame of the video is determined and the corresponding individual position of each calibration reflector for each frame of the recorded frames is used to construct a camera calibration map to calibrate the video camera.

Claims

1. A method for camera calibration comprising:

configuring a calibration target comprising a plurality of calibration reflectors on a test vehicle;

recording a plurality of video frames of said calibration target comprising said plurality of calibration reflectors as they pass through a test scene wherein a position of said calibration target and of each of said calibration reflectors in each frame of said plurality of recorded frames is collected; and

constructing a camera calibration map from said position to calibrate said video camera.

2. The method of claim 1 further comprising:

collecting said video of said test scene with a video camera; and

applying an automated license plate recognition check for each vehicle that enters said test scene until said test vehicle is identified.

3. The method of claim 1 wherein said calibration target is configured to be a grid of at least four calibration reflectors wherein a relative location of each of said plurality of calibration reflectors within said grid is known, and said grid covers as much of a field of view of said test scene as possible.

4. The method of claim 3 wherein identifying a corresponding individual position of each of said calibration reflectors for each frame of said collected video further comprises:

identifying a centroid for each of said calibration reflectors in each frame of said collected video.

5. The method of claim 4 wherein constructing a camera calibration map further comprises:

selecting an arbitrary fixed reference point in said collected video as an origin;

constructing a first calibration map for each frame of said collected video; and

averaging all of said first calibration maps.

6. The method of claim 4 wherein constructing a camera calibration map further comprises:

selecting an arbitrary fixed reference point in said collected video as an origin; and

applying an iterative data alignment and outlier algorithm.

7. The method of claim 1 wherein said collected video comprises a traffic surveillance video feed.

8. The method of claim 7 wherein said test scene comprises one of:

an open roadway;

or

an open traffic intersection.

9. A system for camera calibration comprising:

a calibration target comprising a plurality of calibration reflectors mounted on a test vehicle;

a video camera configured to collect video of a test scene;

a test vehicle identification module configured to identify said test vehicle as it enters said test scene and record a plurality of video frames of said calibration target comprising said plurality of calibration reflectors as they pass through said test scene;

a calibration point identification module configured to detect the position of said calibration target in each frame of said plurality of recorded frames and identify a corresponding individual position of each of said calibration reflectors for each frame of said plurality of recorded frames; and

a camera calibration construction module configured to construct a camera calibration map to calibrate said video camera.

10. The system of claim 9 wherein said test vehicle identification module if further configured to apply an automated license plate recognition check for each vehicle that enters said test scene until said test vehicle is identified.

11. The system of claim 9 wherein said calibration target is configured to be a grid of at least four calibration reflectors wherein a relative location of each of said plurality of calibration reflectors within said grid is known and said grid covers as much of a field of view of said test scene as possible.

12. The system of claim 11 wherein said calibration point identification module is configured to identify a centroid for each of said calibration reflectors in each frame of said collected video.

13. The system of claim 12 wherein said camera calibration construction module is further configured for:

selecting an arbitrary fixed reference point in said collected video as an origin;

constructing a first calibration map for each frame of said collected video; and

averaging all of said first calibration maps.

14. The system of claim 12 wherein said camera calibration construction module is further configured for:

selecting an arbitrary fixed reference point in said collected video as an origin; and

applying an iterative data alignment and outlier algorithm.

15. The system of claim 9 wherein said collected video comprises a traffic surveillance video feed.

16. The system of claim 15 wherein said test scene comprises one of:

an open roadway;

or

an open traffic intersection.

17. A method for camera calibration comprising:

configuring a calibration target comprising a plurality of calibration reflectors on a test vehicle wherein said calibration target is configured to be a grid of calibration reflectors wherein a relative location of each of said plurality of calibration reflectors within said grid is known;

collecting video of a test scene with a video camera;

identifying said test vehicle as it enters said test scene by applying an automated license plate recognition check for each vehicle that enters said test scene until said test vehicle is identified;

recording a plurality of video frames of said calibration target comprising said plurality of calibration reflectors as they pass through said test scene;

detecting the position of said calibration target in each frame of said plurality of recorded frames;

identifying a corresponding individual position of a centroid of each of said calibration reflectors for each frame of said plurality of recorded frames; and

constructing a camera calibration map to calibrate said video camera.

18. The method of claim 17 wherein constructing a camera calibration map further comprises:

selecting an arbitrary fixed reference point in said collected video as an origin;

constructing a first calibration map for each frame of said collected video; and

averaging all of said first calibration maps.

19. The method of claim 17 wherein constructing a camera calibration map further comprises:

selecting an arbitrary fixed reference point in said collected video as an origin; and

applying an iterative data alignment and outlier algorithm.

20. The method of claim 17 wherein said test scene comprises one of:

an open roadway;

or

an open traffic intersection.