Object extraction from video images system and method

• US 9,959,632 B2
• Filed: 03/27/2017
• Issued: 05/01/2018
• Est. Priority Date: 10/27/2014
• Status: Active Grant

• Current Assignee: PlaySight Interactive, Ltd.
• Original Assignee: PlaySight Interactive, Ltd.
• Inventors: Khazanov, Evgeni, Shachar, Chen
• Primary Examiner(s): Kholdebarin, Iman K
• Application Number:
  US15/470,477
• Publication Number:
  US 20170200281A1
• Time in Patent Office: 400 Days
• Field of Search: None
• CPC Class Codes: G06T 2207/10016 Video; Image sequence
• CPC Class Codes: G06T 2207/20224 Image subtraction
• CPC Class Codes: G06T 2207/30221 Sports video; Sports image
• CPC Class Codes: G06T 7/194 involving foreground-background segmentation
• CPC Class Codes: G06T 7/215 Motion-based segmentation
• CPC Class Codes: G06T 7/254 involving subtraction of images
• CPC Class Codes: G06V 20/47 Detecting features for summarising video content

Abstract

A computer implemented method of object extraction from video images, the method comprising steps a computer is programmed to perform, the steps comprising: receiving a plurality of video images, deriving a plurality of background templates from at least one of the received video images, calculating a plurality of differences from an individual one of the received video images, each one of the differences being calculated between the individual video image and a respective and different one of the background templates, and extracting an object of interest from the individual video image, using a rule applied on the calculated differences.

Claims

1. A computer implemented method of object extraction from video images, the method comprising steps a computer is programmed to perform, the steps comprising:

receiving a plurality of video images;

deriving a plurality of background templates from at least one of the received video images;

calculating a plurality of differences from an individual one of the received video images, each one of the differences being calculated between the individual video image and a respective and different one of the background templates; and

extracting an object of interest from the individual video image, using a rule applied on the calculated differences.

2. The method of claim 1, further comprising selecting the applied rule among a plurality of predefined rules.

3. The method of claim 1, further comprising allowing a user to select the applied rule.

4. The method of claim 1, further comprising selecting the applied rule, according to circumstances of capturing of the received video images.

5. The method of claim 1, further comprising selecting the applied rule, according to a characteristic pertaining to the object of interest.

6. The method of claim 1, further comprising selecting the applied rule, according to a characteristic pertaining to a background of the received video images.

7. The method of claim 1, wherein said deriving of the background templates is based on a rule selected among a plurality of predefined rules.

8. The method of claim 1, further comprising allowing a user to select a rule for said deriving of the background templates, wherein said deriving is based on the rule selected by the user.

9. The method of claim 1, wherein said deriving of the background templates is based on a rule selected according to circumstances of capturing of the received video images.

10. The method of claim 1, wherein said deriving of the background templates is based on a rule selected according to a characteristic pertaining to the object of interest.

11. The method of claim 1, wherein said deriving of the background templates is based on a rule selected according to a characteristic pertaining to a background of the received video images.

12. The method of claim 1, further comprising deriving each one of at least two of the background templates, using a respective and different one of a plurality of background calculation methods.

13. The method of claim 1, further comprising deriving each one of at least two of the background templates, using a respective and at least partially different subset of the received video images.

14. The method of claim 1, further comprising deriving each one of at least two of the background templates, using a respective and at least partially less recent subset of the received video images.

15. The method of claim 1, further comprising deriving each one of at least two of the background templates, using a respective and different frequency of sampling of the received video images.

16. The method of claim 1, further comprising deriving each one of at least two of the background templates, using a respective and different in size subset of the received video images.

17. The method of claim 1, further comprising updating each one of at least two of the background templates, with a respective and different update rate.

18. Apparatus for object extraction from video images, the apparatus comprising:

a computer;

a video image receiver, implemented on the computer, configured to receive a plurality of video images;

a background template deriver, in communication with said video image receiver, configured to derive a plurality of background templates from at least one of the received video images;

a difference calculator, in communication with said background template deriver, configured to calculate a plurality of differences from an individual one of the received video images, each one of the differences being calculated between the individual video image and a respective and different one of the background templates; and

an object extractor, in communication with said difference calculator, configured to extract an object of interest from the individual video image, using a rule applied on the calculated differences.

19. A non-transitory computer readable medium storing computer executable instructions for performing steps of object extraction from video images, the steps comprising:

receiving a plurality of video image;

deriving a plurality of background templates from at least one of the received video images;

calculating a plurality of differences from an individual one of the received video images, each one of the differences being calculated between the individual video image and a respective and different one of the background templates; and

extracting an object of interest from the individual video image, using a rule applied on the calculated differences.