METHOD, SYSTEM AND COMPUTER-READABLE MEDIUM FOR RECONSTRUCTING MOVING PATH OF VEHICLE

• US 20120166080A1
• Filed: 06/20/2011
• Published: 06/28/2012
• Est. Priority Date: 12/28/2010
• Status: Abandoned Application

• Current Assignee: Industrial Technology Research Institute
• Original Assignee: Industrial Technology Research Institute
• Inventors: Hung, Shang-Chih, Luo, Yi-Fei, Chen, Jian-Ren, Chen, Luke, Cheng, Chieh-Chen
• Application Number:
  US13/163,753
• Publication Number:
  US 20120166080A1
• Time in Patent Office: Days
• US Class Current: 701/448
• CPC Class Codes: G08G 1/0175 by photographing vehicles, e.g. when violating traffic rules
• CPC Class Codes: G08G 1/20 Monitoring the location of vehicles belonging to a group, e.g. fleet of vehicles, countable or determined number of vehicles
• 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, a system and a computer-readable medium for reconstructing a vehicle moving path are provided. In the method, a plurality of vehicle recognition results of a plurality of first monitoring frames captured by a plurality of first type road monitors are received and compared to find at least one similar vehicle. Next, according to a disposition location of each first road monitor and the comparison result of each vehicle, at least one passing spot and a driving time that each vehicle moves between the disposition locations are estimated. Then, tracking data of at least one moving object appeared in multiple second monitoring frames captured by multiple second type road monitors disposed in the passing spots is inquired. Finally, the vehicles are compared with the tracked moving objects to find the moving object associated with each vehicle, so as to construct a complete moving path of each vehicle.

Claims

1. A method for reconstructing a vehicle moving path, comprising:

receiving vehicle recognition data, wherein the vehicle recognition data comprises a vehicle recognition result of each of a plurality of first monitoring frames captured by a plurality of first type road monitors;

comparing the vehicle recognition result of each of the first monitoring frames to find at least one similar vehicle;

according to a disposition location of each of the first type road monitors and a comparison result of the at least one vehicle, estimating at least one passing spot and a driving time that the at least one vehicle moves between the disposition locations;

inquiring moving object tracking data, wherein the moving object tracking data comprises tracking data of at least one moving object appeared in a plurality of second monitoring frames captured by a plurality of second type road monitors disposed in the at least one passing spot; and

comparing the at least one vehicle with the at least one moving object to find the moving object associated with each of the at least one vehicle, so as to construct a complete moving path of the at least one vehicle.

2. The method for reconstructing the vehicle moving path as claimed in claim 1, wherein the step of comparing the vehicle recognition result of each of the first monitoring frames to find the at least one similar vehicle comprises:

comparing at least one vehicle feature of the vehicles appeared in the first monitoring frames to recognize the at least one similar vehicle.

3. The method for reconstructing the vehicle moving path as claimed in claim 2, wherein the step of comparing the at least one vehicle feature of the vehicles appeared in the first monitoring frames to recognize the at least one similar vehicle comprises:

capturing a first plate number and a second plate number of any two vehicles appeared in the first monitoring frames;

calculating a minimum number of edit operations required for transforming the first plate number to the second plate number, and comparing the minimum number of the edit operations with a threshold value; and

determining the two vehicles to be the similar vehicle when the minimum number of the edit operations is smaller than or equal to the threshold value.

4. The method for reconstructing the vehicle moving path as claimed in claim 2, wherein the at least one vehicle feature comprises a license plate, a vehicle color or a vehicle type.

5. The method for reconstructing the vehicle moving path as claimed in claim 1, wherein the step of estimating the at least one passing spot and the driving time that the at least one vehicle moves between the disposition locations according to the disposition location of each of the first type road monitors and the comparison result of the at least one vehicle comprises:

finding the first monitoring frames where the at least one vehicle appears and the corresponding disposition locations according to the comparison result of the at least one vehicle; and

inquiring historical driving data to determine the at least one passing spot and the driving time that the at least one vehicle moves between the disposition locations, and outputting a driving data collection,

wherein the historical driving data comprises the at least one passing spot and the corresponding driving time that the vehicles used to move between the disposition locations.

6. The method for reconstructing the vehicle moving path as claimed in claim 1, wherein before the step of inquiring the moving object tracking data, the method further comprises:

storing a position, a time, a size, a color and a keyframe of the at least one moving object appeared in the second monitoring frames into a moving object tracking database.

7. The method for reconstructing the vehicle moving path as claimed in claim 6, wherein the step of comparing the at least one vehicle with the at least one moving object to find the moving object associated with the at least one vehicle, so as to construct the complete moving path of the at least one vehicle comprises:

receiving the driving data collection corresponding to each of the at least one vehicle;

sorting the driving data collections according to the driving time of each of the driving data collections;

finding all of the second type road monitors probably passed by according to a geographic position association of the at least one passing spot in the driving data collections;

inquiring the moving object tracking database to obtain the at least one moving object tracking data of the moving object associated with the at least one vehicle according to geographic position data of each of the found second type road monitors; and

constructing the complete moving path of each of the at least one vehicle according to the driving data collection of the at least one vehicle and the at least one moving object tracking data of the moving object associated with the at least one vehicle.

8. The method for reconstructing the vehicle moving path as claimed in claim 7, wherein the step of obtaining the moving object associated with the at least one vehicle comprises:

comparing time information of the at least one vehicle and the at least one moving object to search the moving object with an appearing time closest to a historical statistic time interval, so as to establish association with the at least one vehicle.

9. The method for reconstructing the vehicle moving path as claimed in claim 7, wherein the step of obtaining the moving object associated with each of the at least one vehicle comprises:

comparing space information of the at least one vehicle and the at least one moving object to search the moving object appeared at two adjacent intersections or within a specific distance, so as to establish association with each of the at least one vehicle.

10. The method for reconstructing the vehicle moving path as claimed in claim 7, wherein the step of obtaining the moving object associated with the at least one vehicle comprises:

representing each of the at least one vehicle and each of the at least one moving object by a corresponding feature vector matrix;

obtaining a similarity between each two of the feature vector matrices; and

establishing association between the vehicle and the moving object corresponding to the feature vector matrix having the highest similarity.

11. The method for reconstructing the vehicle moving path as claimed in claim 7, wherein after the step of obtaining the at least one moving object tracking data of the moving object associated with the at least one vehicle, the method further comprises:

deducing a normal moving path according to the at least one passing spot passed by the at least one vehicle and the driving time; and

calculating a difference between the at least one moving object tracking data and the normal moving path to filter out unreasonable moving object tracking data.

12. The method for reconstructing the vehicle moving path as claimed in claim 11, wherein after the step of calculating the difference between the at least one moving object tracking data and the normal moving path to filter out the unreasonable moving object tracking data, the method further comprises:

deducing a possible moving range of the at least one vehicle according to a vehicle speed and a moving direction in a motion model, so as to find a highest possible moving object tracking data from the moving object tracking data already filtering out the unreasonable moving object tracking data.

13. The method for reconstructing the vehicle moving path as claimed in claim 7, wherein after the step of constructing the complete moving path of the at least one vehicle, the method further comprises:

establishing an association between the complete moving path of the at least one vehicle and at least one keyframe to serve as a basis for searching the at least one vehicle according to the vehicle recognition result of each of the first monitoring frames and the at least one keyframe included in the at least one moving object tracking data.

14. The method for reconstructing the vehicle moving path as claimed in claim 1, wherein the first type road monitor supports license plate recognition, and the second type road monitor does not support the license plate recognition.

27. A computer-readable medium, which records a computer program to be loaded into an electronic device to execute the method for reconstructing the vehicle moving path as claimed in claim 1.

15. A system for reconstructing a vehicle moving path, comprising:

a vehicle searching module, configured to receive a vehicle recognition result of each of a plurality of first monitoring frames captured by a plurality of first type road monitors, and compare the vehicle recognition results of the first monitoring frames to find at least one similar vehicle, and according to a disposition location of each of the first type road monitors and a comparison result of the at least one vehicle, estimate at least one passing spot and a driving time that the at least one vehicle moves between the disposition locations; and

a path reconstructing module, configured to inquire tracking data of at least one moving object appeared in a plurality of second monitoring frames captured by a plurality of second type road monitors disposed at the at least one passing spot, and compare the at least one vehicle with the at least one moving object to find the moving object associated with each of the at least one vehicle, so as to construct a complete moving path of the at least one vehicle.

16. The system for reconstructing the vehicle moving path as claimed in claim 15, wherein the vehicle searching module comprises:

a similar vehicle comparison unit, configured to compare at least one vehicle feature of the vehicles appeared in the first monitoring frames to recognize the at least one similar vehicle.

a driving information providing unit, configured to provide historical driving data comprising the at least one passing spot and the corresponding driving time that the vehicles used to move between the disposition locations; and

a passing spot estimation unit, configured to find the first monitoring frames where the at least one vehicle appears and the corresponding disposition locations according to the comparison result of the at least one vehicle, and inquire the historical driving data to determine the at least one passing spot and the driving time that the at least one vehicle moves between the disposition locations, and outputting a driving data collection.

17. The system for reconstructing the vehicle moving path as claimed in claim 16, wherein the similar vehicle comparison unit captures a first plate number and a second plate number of any two vehicles appeared in the first monitoring frames, calculates a minimum number of edit operations required for transforming the first plate number to the second plate number, and compares the minimum number of the edit operations with a threshold value, and determines the two vehicles to be the similar vehicle when the minimum number of the edit operations is smaller than or equal to the threshold value.

18. The system for reconstructing the vehicle moving path as claimed in claim 16, wherein the at least one vehicle feature comprises a license plate, a vehicle color or a vehicle type.

19. The system for reconstructing the vehicle moving path as claimed in claim 15, wherein the path reconstructing module comprises:

a moving object tracking database, configured to store a position, a time, a size, a color and a keyframe of the at least one moving object appeared in the second monitoring frames;

a tracking data inquiry unit, configured to receive the driving data collection corresponding to each of the at least one vehicle, sorting the driving data collections according to the driving time of each of the driving data collections, find all of the second type road monitors probably passed by according to a geographic position association of the at least one passing spot in the driving data collections, and inquire the moving object tracking database to obtain the at least one moving object tracking data of the moving object associated with the at least one vehicle according to geographic position data of each of the found second type road monitors.

20. The system for reconstructing the vehicle moving path as claimed in claim 19, wherein the tracking data inquiry unit compares time information of the at least one vehicle and the at least one moving object to search the moving object with an appearing time closest to a historical statistic time interval, so as to establish association with each of the at least one vehicle.

21. The system for reconstructing the vehicle moving path as claimed in claim 19, wherein the tracking data inquiry unit compares space information of the at least one vehicle and the at least one moving object to search the moving object appeared at two adjacent intersections or within a specific distance, so as to establish association with each of the at least one vehicle.

22. The system for reconstructing the vehicle moving path as claimed in claim 19, wherein the tracking data inquiry unit represents each of the at least one vehicle and each of the at least one moving object by a corresponding feature vector matrix, obtains a similarity between each two of the feature vector matrices, and establishes association between the vehicle and the moving object corresponding to the feature vector matrix having the highest similarity.

23. The system for reconstructing the vehicle moving path as claimed in claim 19, wherein the path reconstructing module further comprises:

a linear regression filter unit, configured to deduce a normal moving path according to the at least one passing spot passed by the at least one vehicle and the driving time, and calculate a difference between the at least one moving object tracking data and the normal moving path to filter out unreasonable moving object tracking data.

24. The system for reconstructing the vehicle moving path as claimed in claim 19, wherein the path reconstructing module further comprises:

a motion model filter unit, configured to deduce a possible moving range of the at least one vehicle according to a vehicle speed and a moving direction in a motion model, so as to find a highest possible moving object tracking data from the moving object tracking data already processed by linear regression filtering.

25. The system for reconstructing the vehicle moving path as claimed in claim 19, further comprising:

a keyframe association module, comprising;

a keyframe database, configured to store at least one keyframe generated according to the vehicle recognition result of each of the first monitoring frames and the at least one moving object tracking data; and

an association establishing unit, configured to establish an association between the complete moving path of the at least one vehicle and at least one keyframe to serve as a basis for searching the at least one vehicle.

26. The system for reconstructing the vehicle moving path as claimed in claim 15, wherein the first type road monitor supports license plate recognition, and the second type road monitor does not support the license plate recognition.