US 11,915,431 B2
Feature point identification in sparse optical flow based tracking in a computer vision system
Deepak Kumar Poddar, Bangalore (IN); Anshu Jain, Bangalore (IN); Desappan Kumar, Bangalore (IN); and Pramod Kumar Swami, Bangalore (IN)
Assigned to Texas Instruments Incorporated, Dallas, TX (US)
Filed by TEXAS INSTRUMENTS INCORPORATED, Dallas, TX (US)
Filed on Aug. 6, 2019, as Appl. No. 16/532,658.
Application 16/532,658 is a continuation of application No. 15/266,149, filed on Sep. 15, 2016, granted, now 10,460,453.
Claims priority of application No. 7079/CHE/2015 (IN), filed on Dec. 30, 2015.
Prior Publication US 2019/0370979 A1, Dec. 5, 2019
Int. Cl. G06T 7/246 (2017.01)
CPC G06T 7/246 (2017.01) [G06T 2200/28 (2013.01); G06T 2207/20016 (2013.01); G06T 2207/30241 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A method comprising:
receiving a first frame;
detecting a first set of feature points within the first frame;
generating a first image that indicates locations of the first set of feature points detected within the first frame, wherein the locations of the first set of feature points are indicated in the first image by a first binary value and a remainder of the first image is indicated by a second binary value;
generating a second image that indicates respective bounded neighborhoods each of which corresponds to a neighborhood surrounding one of a second set of feature points detected based on a second frame, wherein the respective bounded neighborhoods are indicated in the second image by the second binary value and a remainder of the second image is indicated by the first binary value; and
comparing the first image to the second image to generate a third image, wherein locations of a subset of the first set of feature points excluded from the respective bounded neighborhoods are indicated in the third image by a binary value different from a remainder of the third image.