US 12,293,535 B2
Systems and methods for training pose estimators in computer vision
Agastya Kalra, Nepean (CA); Rishav Agarwal, Waterloo (CA); Achuta Kadambi, Los Altos Hills, CA (US); Kartik Venkataraman, San Jose, CA (US); and Anton Boykov, Waterloo (CA)
Assigned to Intrinsic Innovation LLC, Mountain View, CA (US)
Filed by INTRINSIC INNOVATION LLC, Mountain View, CA (US)
Filed on Aug. 3, 2021, as Appl. No. 17/393,338.
Prior Publication US 2023/0041560 A1, Feb. 9, 2023
Int. Cl. G06T 7/70 (2017.01); H04N 13/243 (2018.01); H04N 23/56 (2023.01); H04N 25/705 (2023.01)
CPC G06T 7/70 (2017.01) [H04N 13/243 (2018.05); H04N 23/56 (2023.01); H04N 25/705 (2023.01); G06T 2200/08 (2013.01); G06T 2207/20081 (2013.01)] 21 Claims
OG exemplary drawing
 
1. A method of capturing training data in a data capture stage, the method comprising:
initiating capture of a first image of a target object by a first camera of the data capture stage;
initiating capture of a second image of the target object by a second camera of the data capture stage;
receiving a first pose of the target object corresponding to a first viewpoint of the first image;
projecting, using calibration data between the first camera and the second camera, the first pose into a coordinate system of the second camera to generate a second pose of the target object corresponding to a second viewpoint of the second image;
generating a second label associated with the second image, the second label comprising the second pose; and
generating the training data based on the second image and the second label.