IP Library Granted Patent US 10,529,080
Granted Patent B2
US 10,529,080 · App. 16/014,848 · Granted Jan 7, 2020

Automatic thoroughfare recognition and traffic counting

Inventor: Renat Idrisov (Berlin, DE)
Assignee: SATORI WORLDWIDE, LLC
G06T7/285G06K9/00771G06K9/00798G06K9/4652G06T7/246G08G1/005G08G1/015G08G1/0116G08G1/0133G08G1/0141G08G1/04G08G1/065G08G1/127G06T2207/10021G06T2207/30236G06T2207/30241G06T2207/30252
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Quick Facts
Patent No.
US 10,529,080
App. No.
16/014,848
Granted
Jan 7, 2020
Kind
B2
Abstract

Methods and systems for road recognition and traffic counting for complex thoroughfares are described. The method includes receiving a set of video frames captured by one or more electronic devices. The set of video frames includes a capture of a thoroughfare. The method further includes identifying an object featured in each respective video frame of a subset of the set of video frames, generating a plurality of vectors corresponding to a direction of motion of the object, combining intersecting vectors of the plurality of vectors, and generating a graphical map of at least one road in the thoroughfare based at least in part on the combination of intersecting vectors.

Claims (40)

1. A method, comprising:

receiving, by a computer processing device, a set of video frames captured by one or more electronic devices, the set of video frames comprising a capture of a thoroughfare;

identifying, by the computer processing device, an object featured in each respective video frame of a subset of the set of video frames;

generating, by the computer processing device, a plurality of vectors corresponding to a direction of motion of the object;

combining, by the computer processing device, intersecting vectors of the plurality of vectors corresponding to the direction of motion of the object; and

generating, by the computer processing device, a graphical map of at least one road in the thoroughfare based at least in part on the combination of intersecting vectors.

2. The method of claim 1 , comprising determining the direction of motion of the object biased at least in part on a comparison of the object with respect to each video frame of the subset of video frames.

3. The method of claim 1 , wherein identifying the object featured in each respective video frame of the subset of video frames comprises identifying a vehicle in each respective video frame.

4. The method of claim 1 , wherein identifying the object featured in each respective video frame of the subset of video frames comprises identifying a color of the object.

5. The method of claim 1 , wherein identifying the object featured in each respective video frame of the subset of video frames comprises identifying a size of the object.

6. The method of claim 1 , wherein generating the plurality of vectors comprises:

generating a respective pair of vectors for the object being identified in each of the subset of video frames, the subset of video frames including three most recent video frames of the set of video frames; and

determining the direction of motion of the object based at least in part on an angle of each respective pair of vectors.

7. The method of claim 1 , comprising:

generating a counting indicator on the graphical map, the counting indicator comprising a midpoint of the at least one road; and

incrementing a counter when the object is determined to traverse the counting indicator on the graphical map.

8. The method of claim 1 , wherein the set of video frames comprises N number of video frames, and wherein the plurality of vectors comprises N−1 number of vectors.

9. An apparatus, comprising:

a computer processing device to:

receive a set of video frames captured by one or more electronic devices, the set of video frames video frames comprising a capture of a thoroughfare;

identify an object featured in each respective video frame of a subset of the set of video frames;

generate a plurality of vectors corresponding to a direction of motion of the object;

combine intersecting vectors of the plurality of vectors corresponding to the direction of motion of the object; and

generate a graphical map of at least one road in the thoroughfare based at least in part on the combination of intersecting vectors.

10. The apparatus of claim 9 , wherein the computer processing device is to determine the direction of motion of the object based at least in part on a comparison of the object with respect to each video frame of the subset of video frames.

11. The apparatus of claim 9 , wherein to identify the object featured in each respective video frame of the subset of video frames, the computer processing device is to identify a vehicle in each respective video frame.

12. The apparatus of claim 9 , wherein to identify the object featured in each respective video frame of the subset of video frames, the computer processing device is to identify a color of the object.

13. The apparatus of claim 9 , wherein to identify the object featured in each respective video frame of the subset of video frames, the computer processing device is to identify a size of the object.

14. The apparatus of claim 9 , wherein the set of video frames comprises N number of video frames, and wherein the plurality of vectors comprises N−1 number of vectors.

15. A non-transitory computer-readable storage medium including instructions that, when executed by a computer processing device, cause the computer processing device to:

receive a set of video frames captured by one or more electronic devices, the set of video frames video frames comprising a capture of a thoroughfare;

identify a object featured in each respective video frame of a subset of the set of video frames;

generate a plurality of vectors corresponding to a direction of motion of the object;

combine intersecting vectors of the plurality of vectors corresponding to the direction of motion of the object; and

generate a graphical map of at least one road in the thoroughfare based at least in part on the combination of intersecting vectors.

16. The non-transitory computer-readable storage medium of claim 15 , wherein the computer processing device is to determine the direction of motion of the object based at least in part on a comparison of the object with respect to each video frame of the subset of video frames.

17. The non-transitory computer-readable storage medium of claim 15 , wherein to identify the object featured in each respective video frame of the subset of video frames, the computer processing device is to identify a vehicle in each respective video frame.

18. The non-transitory computer-readable storage medium of claim 15 , wherein to identify the object featured in each respective video frame of the subset of video frames, the computer processing device is to identify a color of the object.

19. The non-transitory computer-readable storage medium of claim 15 , wherein to identify the object featured in each respective video frame of the subset of video frames, the computer processing device is to identify a size of the object.

20. The non-transitory computer-readable storage medium of claim 15 , wherein the set of video frames comprises N number of video frames, and wherein the plurality of vectors comprises N−1 number of vectors.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jul 18, 2018
From: IDRISOV, RENAT
To: SATORI WORLDWIDE, LLC
Reel/Frame 046387/0325 →
Continuity (2)
Provisional Application 62524354 · Jun 23, 2017
Related Publication 20180374223A1 · Dec 27, 2018