	US 12,106,486 B2
	Whole body visual effects
Gal Dudovitch, Tel Aviv (IL); Peleg Harel, Ramat Gan (IL); Chia-Hao Hsieh, Los Angeles, CA (US); Sergei Korolev, Marina del Rey, CA (US); and Ma'ayan Shuvi, Tel Aviv (IL)
Assigned to SNAP INC., Santa Monica, CA (US)
Filed by Snap Inc., Santa Monica, CA (US)
Filed on Feb. 24, 2021, as Appl. No. 17/249,241.
Prior Publication US 2022/0270265 A1, Aug. 25, 2022
Int. Cl. G06T 7/194 (2017.01); G06F 3/04842 (2022.01); G06F 3/04845 (2022.01); G06T 7/11 (2017.01); G06T 7/13 (2017.01); G06T 11/60 (2006.01)

CPC G06T 7/194 (2017.01) [G06F 3/04842 (2013.01); G06F 3/04845 (2013.01); G06T 7/11 (2017.01); G06T 7/13 (2017.01); G06T 11/60 (2013.01); G06T 2207/20081 (2013.01)]

20 Claims

1. A method comprising:

receiving, by one or more processors, a monocular image that includes a depiction of a whole body of a user;

generating a segmentation of the whole body of the user based on the monocular image by:

generating the segmentation by a first machine learning model; and

smoothing the segmentation by a second machine learning model that predicts a segmentation based on depiction of whole bodies in a plurality of monocular images received prior to the monocular image;

receiving input that selects a visualization mode; and

applying one or more visual effects corresponding to the visualization mode to the monocular image based on the segmentation.