US 11,893,808 B2
Learning-based 3D property extraction
Swupnil Kumar Sahai, Menlo Park, CA (US); Richard Hsu, Irvine, CA (US); Adith Balamurugan, Plano, TX (US); and Neel Sesh Ramachandran, Los Altos, CA (US)
Assigned to Mangolytics, Inc., Saratoga, CA (US)
Filed by Mangolytics, Inc., Saratoga, CA (US)
Filed on Nov. 30, 2020, as Appl. No. 17/106,499.
Prior Publication US 2022/0171957 A1, Jun. 2, 2022
Int. Cl. G06V 20/64 (2022.01); G06N 3/04 (2023.01); G06N 3/08 (2023.01); G06V 20/10 (2022.01); G06V 20/40 (2022.01); G06F 18/214 (2023.01)
CPC G06V 20/64 (2022.01) [G06F 18/214 (2023.01); G06N 3/04 (2013.01); G06N 3/08 (2013.01); G06V 20/10 (2022.01); G06V 20/42 (2022.01)] 20 Claims
OG exemplary drawing
 
1. A mobile device, comprising:
a camera that captures a 2D image of a participatory event including at least a portion of a reference visual feature of the participatory event and at least a portion of an object of interest in the participatory event; and
a neural network trained to extract from the 2D image a 3D property of the object within a 3D space of the participatory event by correlating an arrangement of pixels in the 2D image that correspond to the object and an arrangement of pixels in the 2D image that correspond to the reference visual feature to the 3D property.