US 12,405,660 B2
Gaze estimation using one or more neural networks
Michael Stengel, Cupertino, CA (US); Morgan McGuire, Waterloo (CA); Alexander Majercik, San Francisco, CA (US); and David Luebke, Charlottesville, VA (US)
Assigned to NVIDIA Corporation, Santa Clara, CA (US)
Filed by Nvidia Corporation, Santa Clara, CA (US)
Filed on May 11, 2020, as Appl. No. 16/872,069.
Prior Publication US 2021/0350550 A1, Nov. 11, 2021
Int. Cl. G06K 9/00 (2022.01); G06F 3/01 (2006.01); G06N 3/08 (2023.01); G06T 7/246 (2017.01); G06T 7/70 (2017.01); G06V 10/82 (2022.01); G06V 20/20 (2022.01); G06V 40/19 (2022.01)
CPC G06F 3/013 (2013.01) [G06N 3/08 (2013.01); G06T 7/246 (2017.01); G06T 7/70 (2017.01); G06V 10/82 (2022.01); G06V 20/20 (2022.01); G06V 40/19 (2022.01); G06T 2207/10016 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/30201 (2013.01)] 31 Claims
OG exemplary drawing
 
1. One or more processors, comprising:
circuitry to use an amount by which a first image has changed from a second image to select whether to use one or more first portions of one or more neural networks to generate a coarse estimate of a location of one or more pupils within the first image, wherein one or more second portions of the one or neural networks are used to generate a fine estimate of the location of the one or more pupils within the first image using a prior estimate from the second image when the amount is below a threshold amount.