Technical Papers

Date/Time: 04 – 13 December 2020
All presentations are available in the virtual platform on-demand.

Lecturer(s):
Breannan Smith, Facebook Reality Labs, United States of America
Chenglei Wu, Facebook Reality Labs, United States of America
He Wen, Facebook Reality Labs, United States of America
Patrick Peluse, Facebook Reality Labs, United States of America
Yaser Sheikh, Facebook Reality Labs, United States of America
Jessica Hodgins, Facebook AI Research, United States of America
Takaaki Shiratori, Facebook Reality Labs, United States of America

Bio:

Description: Many of the actions that we take with our hands involve self-contact and occlusion: shaking hands, making a fist, or interlacing our fingers while thinking. This use of of our hands illustrates the importance of tracking hands through self-contact and occlusion for many applications in computer vision and graphics, but existing methods for tracking hands and faces are not designed to treat the extreme amounts of self-contact and self-occlusion exhibited by common hand gestures. By extending recent advances in vision-based tracking and physically based animation, we present the first algorithm capable of tracking high-fidelity hand deformations through highly self-contacting and self-occluding hand gestures, for both single hands and two hands. By constraining a vision-based tracking algorithm with a physically based deformable model, we obtain an algorithm that is robust to the ubiquitous self-interactions and massive self-occlusions exhibited by common hand gestures, allowing us to track two hand interactions and some of the most difficult possible configurations of a human hand.