Reconstructing Hand Shape and Appearance for Accurate Tracking from Monocular Video
SessionDoctoral Consortium
DescriptionIn this thesis, we 1) introduce a novel hand shape model that augments a data-driven shape model and adapt its local scale to represent unseen hand shapes, 2) propose a method to reconstruct a detailed hand avatar from monocular RGB video captured under real-world environment lighting by jointly optimizing shape, appearance, and lighting parameters using a realistic shading model in a differentiable rendering framework incorporating Monte Carlo path tracing, and 3) present a robust hand tracking framework that accurately registers our hand model to monocular depth data utilizing a modified skinning function with blend shapes.
Event Type
Doctoral Consortium
TimeFriday, 15 December 202311:00am - 11:30am
LocationMeeting Room C4.3, Level 4 (Convention Centre)
