REAL-TIME VIDEO TRIGGERING FOR TRAFFIC SURVEILANCE AND PHOTO ENFORCEMENT APPLICATIONS USING NEAR INFRARED VIDEO ACQUISITION

• US 20130278761A1
• Filed: 04/23/2012
• Published: 10/24/2013
• Est. Priority Date: 04/23/2012
• Status: Active Grant

• Current Assignee: Conduent Business Services, LLC (Conduent, Inc.)
• Original Assignee: Xerox Corporation (Xerox Holdings Corp.)
• Inventors: Wu, Wencheng
• Granted Patent: US 10,713,499 B2
• Time in Patent Office: Days
• US Class Current: 348/143
• CPC Class Codes: G06V 10/143 Sensing or illuminating at different wavelengths
• CPC Class Codes: G06V 20/54 of traffic, e.g. cars on the road, trains or boats
• CPC Class Codes: G06V 20/62 Text, e.g. of license plates, overlay texts or captions on TV images
• CPC Class Codes: H04N 7/18 Closed-circuit television [CCTV] systems, i.e. systems in which the video signal is not broadcast

Abstract

A method and system for real-time video triggering for traffic surveillance and photo enforcement comprises receiving a streaming video feed and performing a spatial uniformity correction on each frame of the streaming video feed and resampling the video feed to a lower spatial resolution. Motion blobs are then detected. Next a three-layered approach is used to identify candidate motion blobs which can be output to a triggering module to trigger a video collection action.

Claims

1. A method for real-time video triggering comprising:

receiving a streaming video feed;

resampling said streaming video to a lower spatial resolution of said streaming video;

detecting a plurality of motion blobs in said resampled video stream;

identifying candidate motion blobs from said plurality of motion blobs as candidates for triggering a video collection action;

outputting said candidate motion blobs; and

triggering a collection action.

2. The method of claim 1 wherein said streaming video feed comprises high-resolution near infrared streaming video.

3. The method of claim 2 wherein detecting a plurality of motion blobs in said resampled video stream further comprises at least one of:

analyzing said resampled video using bi-directional frame to frame differences;

labeling an initial foreground and background in said resampled video stream; and

applying morphological filtering to said labeled video frame to identify a plurality of motion blobs in said resampled video stream.

4. The method of claim 3 wherein indentifying candidate motion blobs from said plurality of motion blobs as candidates for triggering a video collection action further comprises:

eliminating any motion blob from said plurality of motion blobs in said resampled video stream as a candidate motion blob if a size and aspect ratio of said motion blob are not within a predefined size and aspect ratio range;

eliminating any motion blob from said remaining plurality of motion blobs at original resolution as a candidate motion blob if a standard deviation of an intensity of said motion blob does not fit a predefined characteristic signature; and

eliminating a motion blob from said remaining plurality of motion blobs at original resolution as a candidate motion blob if said motion blob is not identified as a candidate motion blob by a candidate motion blob classifier.

5. The method of claim 4 wherein outputting said candidate motion blobs further comprises:

outputting a plurality of coordinates of centroids and a bounding box associated with said candidate motion blobs.

6. The method of claim 5 wherein said candidate motion blobs comprise license plates.

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

8. The method of claim 1 further comprising:

performing a spatial uniformity correction on each frame of said streaming video feed wherein said spatial uniformity correction performed on each frame of said streaming video feed is only performed when an associated ambient light level is low.

9. A system for real-time video triggering comprising:

a video camera;

a video receiving module for receiving a streaming video feed from said video camera;

a resampling module configured to receive said streaming video feed and resample said streaming video to a lower spatial resolution of said streaming video;

a detection module configured to detect a plurality of motion blobs in said resampled video stream;

an identification module configured to identify candidate motion blobs from said plurality of motion blobs as candidates for triggering a video collection action; and

an output module wherein said candidate motion blobs are provided to a triggering module configured to trigger a collection action.

10. The system of claim 9 wherein said video camera is configured to collect high-resolution near infrared streaming video.

11. The system of claim 10 wherein said detection module is further configured to:

analyze said resampled video using bi-directional frame to frame differences;

label an initial foreground and background in said resampled video stream; and

apply morphological filtering to said labeled video frame to identify a plurality of motion blobs in said resampled video stream.

12. The system of claim 11 wherein identification module is further configured to:

eliminate any motion blob from said plurality of motion blobs in said resampled video stream as a candidate motion blob if a size and aspect ratio of said motion blob are not within a predefined size and aspect ratio range;

eliminate any motion blob from said remaining plurality of motion blobs at original resolution as a candidate motion blob if a standard deviation of an intensity of said motion blob does not fit a predefined characteristic signature; and

eliminate a motion blob from said remaining plurality of motion blobs at original resolution as a candidate motion blob if said motion blob is not identified as a candidate motion blob by a candidate motion blob classifier.

13. The system of claim 12 wherein output module is further configured to:

output a plurality of coordinates of centroids and a bounding box associated with said candidate motion blobs to a triggering module.

14. The system of claim 13 wherein said candidate motion blobs comprise license plates.

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

16. The system of claim 9 further comprising a spatial uniformity correction module wherein a spatial uniformity correction is applied to said streaming video feed and said spatial uniformity correction preformed on each frame of said streaming video feed is only performed when an associated ambient light level is low.

17. A computer program product comprising:

a computer-usable data carrier storing instructions that, when executed by a computer, cause the computer to perform a method of rear-time video triggering, the method comprising;

receiving a streaming video feed;

resampling said streaming video to a lower spatial resolution of said streaming video;

detecting a plurality of motion blobs in said resampled video stream by at least one of;

analyzing said resampled video using bi-directional frame to frame differences;

labeling an initial foreground and background in said resampled video stream; and

applying morphological filtering to said resampled video stream to identify a plurality of motion blobs in said resampled video stream;

eliminating any motion blob from said plurality of motion blobs in said resampled video stream as a candidate motion blob if a size and aspect ratio of said motion blob are not within a predefined size and aspect ratio range;

eliminating any motion blob from said remaining plurality of motion blobs at original resolution as a candidate motion blob if a standard deviation of an intensity of said motion blob does not fit a predefined characteristic signature;

eliminating a motion blob from said remaining plurality of motion blobs at original resolution as a candidate motion blob if said motion blob is not identified as a candidate motion blob by a candidate motion blob classifier video stream as candidates for triggering a video collection action;

outputting a plurality of coordinates of centroids and a bounding box associated with said candidate motion blobs; and

triggering a video collection action.

18. The computer program product of claim 17, wherein said streaming video feed comprises high-resolution near infrared streaming video.

19. The computer program product of claim 18, wherein said candidate motion blobs comprise license plates.

20. The method of claim 18, wherein said spatial uniformity correction preformed on each frame of said streaming video feed is only performed when an associated ambient light level is low.