TRACKING HUMANS IN VIDEO IMAGES

• US 20160092727A1
• Filed: 09/30/2014
• Published: 03/31/2016
• Est. Priority Date: 09/30/2014
• Status: Abandoned Application

• Current Assignee: Alcatel-Lucent USA, Inc. (Nokia Corporation)
• Original Assignee: Alcatel-Lucent USA, Inc. (Nokia Corporation)
• Inventors: Ren, Yansong, Woo, Thomas
• Application Number:
  US14/502,806
• Publication Number:
  US 20160092727A1
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06T 2207/10016 Video; Image sequence
• CPC Class Codes: G06T 2207/30196 Human being; Person
• CPC Class Codes: G06T 2207/30232 Surveillance
• CPC Class Codes: G06T 7/11 Region-based segmentation
• CPC Class Codes: G06T 7/194 involving foreground-background segmentation
• CPC Class Codes: G06T 7/74 involving reference images or patches
• CPC Class Codes: G06V 10/462 Salient features, e.g. scale invariant feature transforms [SIFT]
• 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 40/103 Static body considered as a whole, e.g. static pedestrian or occupant recognition

Abstract

A processor accesses a first video image and a second video image from a sequence of video images and applies a patch descriptor technique to determine a first portion of the first video image that encompasses a first person. The processor determines a location of the first person in the second video image by comparing keypoints in the first portion of the first video image to one or more keypoints in the second video image.

Claims

1. A method comprising:

accessing a first video image and a second video image from a sequence of video images;

applying a patch descriptor technique to determine a first portion of the first video image that encompasses a first person; and

determining a location of the first person in the second video image by comparing keypoints in the first portion of the first video image to at least one keypoint in the second video image.

2. The method of claim 1, further comprising:

determining a background video image based on a subset of the sequence of video images; and

generating first and second foreground video images by subtracting the background video image from the first and second video images.

3. The method of claim 2, wherein applying the patch descriptor technique comprises applying the patch descriptor technique to the first foreground video image to determine the first portion that encompasses the first person.

4. The method of claim 3, further comprising:

determining the keypoints in the first portion of the first video image and the at least one keypoint in the second video image using the first foreground video image and the second foreground video image, respectively.

5. The method of claim 1, wherein determining the location of the first person in the second video image comprises comparing keypoints in the first portion of the first video image to at least one keypoint in a second portion of the second video image determined using the patch descriptor technique and determining that the second portion encompasses the first person in response to a percentage of matching keypoints in the first portion and the second portion exceeding a threshold.

6. The method of claim 5, wherein determining the location of the first person in the second video image comprises determining that the first person is not visible in the second video image in response to a percentage of the keypoints in the first portion of the first video that matches the at least one keypoint in the second portion being below the threshold.

7. The method of claim 5, further comprising:

determining the second portion of the second video image based on at least one of the first portion of the first video image and a motion history associated with the first portion of the first video image.

8. The method of claim 1, further comprising:

generating a motion history for the first person in response to determining the location of the first person in the second video image.

9. The method of claim 1, further comprising:

identifying a third person in the second video image by comparing the keypoints in the first video image to at least one keypoint in a candidate region in the second video image, wherein the third person is not identified in the first video image by the patch descriptor technique.

10. An apparatus comprising:

a memory to store a first video image and a second video image from a sequence of video images; and

at least one processor to apply a patch descriptor technique to the first video image and the second video image to determine a first portion of the first video image that encompasses a first person and to determine a location of the first person in the second video image by comparing keypoints in the first portion of the first video image to at least one keypoint in the second video image.

11. The apparatus of claim 10, wherein the at least one processor is to determine a background image based on a subset of the sequence of video images and generate first and second foreground video images by subtracting the background image from the first and second video images.

12. The apparatus of claim 11, wherein the at least one processor is to apply the patch descriptor technique to the first foreground video image to determine the first portion that encompasses the first person.

13. The apparatus of claim 12, wherein the at least one processor is to determine the keypoints in the first portion of the first video image and the at least one keypoint in the second video image using the first foreground video image and the second foreground video image, respectively.

14. The apparatus of claim 10, wherein the at least one processor is to compare keypoints in the first portion of the first video image to at least one keypoint in a second portion of the second video image determined using the patch descriptor technique and determine that the second portion encompasses the first person in response to a percentage of matching keypoints in the first portion and the second portion exceeding a threshold.

15. The apparatus of claim 14, wherein the at least one processor is to determine that the first person is not visible in the second video image in response to a percentage of the keypoints in the first portion of the first video that matches the at least one keypoint in the second portion being below the threshold.

16. The apparatus of claim 14, wherein the at least one processor is to determine the second portion of the second video image based on at least one of the first portion of the first video image and a motion history associated with the first portion of the first video image.

17. The apparatus of claim 10, wherein the at least one processor is to generate a motion history for the first person in response to determining the location of the first person in the second video image.

18. The apparatus of claim 10, wherein the at least one processor is to identify a third person in the second video image by comparing the keypoints in the first video image to at least one keypoint in a candidate region in the second video image, wherein the third person is not identified in the first video image by the patch descriptor technique.

19. A non-transitory computer readable medium embodying a set of executable instructions, the set of executable instructions to manipulate at least one processor to:

access a first video image and a second video image from a sequence of video images;

apply a patch descriptor technique to determine a first portion of the first video image that encompasses a first person; and

determine a location of the first person in the second video image by comparing keypoints in the first portion of the first video image to at least one keypoint in the second video image.

20. The non-transitory computer readable medium of claim 19, wherein the set of executable instructions is to manipulate the at least one processor to compare keypoints in the first portion of the first video image to at least one keypoint in a second portion of the second video image determined using the patch descriptor technique and determine that the second portion encompasses the first person in response to a percentage of matching keypoints in the first portion and the second portion exceeding a threshold.