BUS LANE INFRACTION DETECTION METHOD AND SYSTEM

• US 20150117704A1
• Filed: 10/31/2013
• Published: 04/30/2015
• Est. Priority Date: 09/13/2012
• Status: Active Grant

• Current Assignee: Conduent Business Services, LLC (Conduent, Inc.)
• Original Assignee: Xerox Corporation (Xerox Holdings Corp.)
• Inventors: Bernal, Edgar A., Loce, Robert P., Bulan, Orhan
• Granted Patent: US 9,442,176 B2
• Time in Patent Office: Days
• US Class Current: 382/103
• CPC Class Codes: G01S 3/7864 T.V. type tracking systems
• CPC Class Codes: G06F 18/23 Clustering techniques
• CPC Class Codes: G06T 2207/30236 Traffic on road, railway or crossing
• CPC Class Codes: G06T 7/20 Analysis of motion motion estimation for coding, decoding, compressing or decompressing digital video signals H04N19/43, H04N19/51
• CPC Class Codes: G06T 7/215 Motion-based segmentation
• CPC Class Codes: G06T 7/223 using block-matching
• CPC Class Codes: G06T 7/246 using feature-based methods, e.g. the tracking of corners or segments
• CPC Class Codes: G06T 7/269 using gradient-based methods
• CPC Class Codes: G06V 20/52 Surveillance or monitoring of activities, e.g. for recognising suspicious objects recognising microscopic objects G06V20/69
• CPC Class Codes: G06V 20/54 of traffic, e.g. cars on the road, trains or boats
• CPC Class Codes: G08G 1/0175 by photographing vehicles, e.g. when violating traffic rules
• CPC Class Codes: G08G 1/04 using optical or ultrasonic detectors
• CPC Class Codes: G08G 1/096716 where the received information does not generate an automatic action on the vehicle control
• CPC Class Codes: G08G 1/096741 where the source of the transmitted information selects which information to transmit to each vehicle
• CPC Class Codes: G08G 1/096783 where the origin of the information is a roadside individual element
• CPC Class Codes: H04N 19/139 Analysis of motion vectors, e.g. their magnitude, direction, variance or reliability
• CPC Class Codes: H04N 19/513 Processing of motion vectors

Abstract

This disclosure provides methods and systems for form a trajectory of a moving vehicle captured with an image capturing device. According to one exemplary embodiment, a method forms a trajectory of a moving vehicle and determines if the vehicle is moving in one of a permitted manner and an unpermitted manner relative to the appropriate motor vehicle lane restriction laws and/or regulations.

Claims

1. A computer implemented method of estimating a trajectory of a moving vehicle captured with an image capturing device and determining if the moving vehicle is moving in one of a permitted manner and an unpermitted manner, the image capturing device oriented to include a field of view spanning a vehicle detection target region, the method comprising:

a) acquiring a first set of motion vectors based on a plurality of frames captured with the image capturing device, the first set of motion vectors including a coherent cluster of motion vectors representative of the moving vehicle detected within the vehicle detection target region at a first location;

b) acquiring a second set of motion vectors based on the plurality of frames captured with the image capturing device, the second set of motion vectors including a coherent cluster of motion vectors representative of the moving vehicle detected within the vehicle detection target region at a second location different from the first location;

c) estimating a trajectory of the moving vehicle detection within the vehicle detection target region based on the first location and the second location; and

d) analyzing the estimated trajectory of the moving vehicle to determine if the moving vehicle is moving in one of the permitted manner and the unpermitted manner.

2. The computer implemented method according to claim 1, wherein the permitted manner and unpermitted manner are associated with motor vehicle lane restrictions.

3. The computer implemented method according to claim 2, further comprising:

classifying the moving vehicle as one or more of a relatively large size vehicle, a relatively small size vehicle, a truck, a bus, a non-bus vehicle, a passenger vehicle and a motor cycle, and

step d) analyzes the estimated trajectory of the moving vehicle to determine if the moving vehicle is moving in one of a permitted manner and an unpermitted manner associated with motor vehicle lane restrictions associated with the moving vehicle classification.

4. The computer implemented method according to claim 2 classifying the moving vehicle as one of a bus and a non-bus vehicle, and;

step d) analyzes the estimated trajectory of the moving vehicle to determine if the moving vehicle is moving in one of a permitted manner and unpermitted manner associated with motor vehicle lane restrictions associated with the moving vehicle classification,

wherein the motor vehicle lane restriction permits only moving buses and other moving non-bus vehicle classifications if the other moving non-bus vehicle turns right from the bus lane.

5. The computer implemented method according to claim 1, wherein step d) compares the estimated trajectory with a plurality of predefined patterns to determine if the moving vehicle is moving in one of a permitted manner and an unpermitted manner.

6. The computer implemented method according to claim 1, further comprising:

e) generating a violation signal if the moving vehicle is moving in an unpermitted manner.

7. The computer implemented method according to claim 1, wherein the first and second set of motion vectors are compression type motion vectors.

8. The computer implemented method according to claim 1, wherein the image capturing device is one of a visible light video camera, infrared video camera, thermal video camera and satellite imaging video camera.

9. The computer implemented method according to claim 1, wherein, prior to step a), the method comprises:

generating a compressed video stream of video frames captured with the image capturing device, the compressed video stream including compression type motion vectors subsequently acquired in steps a) and b).

10. The computer implemented method according to claim 1, wherein step a) and step b) extract a first set of compression type motion vectors and second set of compression type motion vectors, respectively, from a compressed video stream including a moving vehicle captured with the image capturing device.

11. An image processing system comprising:

an image capturing device oriented to include a field of view spanning a vehicle detection target region, and

an image processor operatively associated with the image capturing device, the image processor configured to perform a method of estimating a trajectory of a moving vehicle captured with the image capturing device and determining if the moving vehicle is moving in one of a permitted manner and an unpermitted manner, the method comprising;

a) acquiring a first set of motion vectors based on a plurality of frames captured with the image capturing device, the first set of motion vectors including a coherent cluster of motion vectors representative of the moving vehicle detected within the vehicle detection target region at a first location;

b) acquiring a second set of motion vectors based on the plurality of frames captured with the image capturing device, the second set of motion vectors including a coherent cluster of motion vectors representative of the moving vehicle detected within the vehicle detection target region at a second location different from the first location;

c) estimating a trajectory of the moving vehicle detection within the vehicle detection target region based on the first location and the second location; and

d) analyzing the estimated trajectory of the moving vehicle to determine if the moving vehicle is moving in one of the permitted manner and the unpermitted manner.

12. The imaging processing system according to claim 11, wherein the permitted manner and unpermitted manner are associated with motor vehicle lane restrictions.

13. The image processing system according to claim 12, the method further comprising:

classifying the moving vehicle as one or more of a relatively large size vehicle, a relatively small size vehicle, a truck, a bus, a non-bus vehicle, a passenger vehicle and a motor cycle, and

step d) analyzes the estimated trajectory of the moving vehicle to determine if the moving vehicle and associated moving vehicle classification is moving in one of a permitted manner and an unpermitted manner associated with motor vehicle lane restrictions associated with the moving vehicle classification.

14. The image processing system according to claim 13, wherein the motor vehicle lane restriction permits only moving buses and other moving non-bus vehicle classifications if the other moving non-bus vehicle turns right from the bus lane.

15. The image processing system according to claim 11, wherein step d) compares the estimated trajectory with a plurality of predefined patterns to determine if the moving vehicle is moving in one of a permitted manner and an unpermitted manner.

16. The image processing system according to claim 11, the method further comprising:

e) generating a violation signal if the moving vehicle is moving in an unpermitted manner.

17. The image processing system according to claim 11, wherein the first and second set of motion vectors are compression type motion vectors.

18. The image processing system according to claim 11, wherein the image capturing device is one of a visible light video camera, infrared video camera, thermal video camera and satellite imaging video camera.

19. The image processing system according to claim 11, wherein, prior to step a), the method comprises:

generating a compressed video stream of video frames captured with the image capturing device, the compressed video stream including compression type motion vectors subsequently acquired in steps a) and b).

20. The image processing system according to claim 11, wherein step a) and step b) extract a first set of compression type motion vectors and second set of compression type motion vectors, respectively, from a compressed video stream including a moving vehicle captured with the image capturing device.

21. A computer implemented method of detecting a moving vehicle violation of a motor vehicle lane restriction, the moving vehicle captured with an image capturing device, the image capturing device oriented to include a field of view spanning a vehicle detection target region, the method comprising:

a) acquiring compressed video of a moving vehicle captured with the image capturing device, the compressed video including compression type motion vectors representing movement of the moving vehicle;

b) classifying the moving vehicle as one or more of a large size vehicle, a relatively small size vehicle, a truck, a bus, a non-bus vehicle, a passenger vehicle and a motorcycle;

c) estimating a trajectory of the moving vehicle based on a track of the moving vehicle represented as a plurality of temporal spaced coherent clusters of motion vectors associated with the moving vehicle; and

d) analyzing the moving vehicle classification and the estimated trajectory to determine if the moving vehicle is in violation of the motor vehicle lane restriction.

22. The computer implemented method according to claim 21, wherein the motor vehicle lane restriction permits only moving buses and other moving non-bus vehicle classifications if the other moving non-bus vehicle turns right from the bus lane.

23. The computer implemented method according to claim 21, wherein step d) compares the estimated trajectory with a plurality of predefined patterns to determine if the moving vehicle is in violation of the motor vehicle lane restriction.

24. The computer implemented method according to claim 21, further comprising:

e) generating a violation signal if the moving vehicle is in violation of the motor vehicle lane restriction.

25. The computer implemented method according to claim 21, wherein prior to step a), the method comprises:

generating a compressed video stream of video frames captured with the image capturing device, the compressed video stream including compression type motion vectors subsequently acquired in step a).