Total Capture: A 3D Deformation Model for
Tracking Faces, Hands, and Bodies

Hanbyul Joo, Tomas Simon, and Yaser Sheikh

Carnegie Mellon University

CVPR Best Student Paper Award


Abstract

We present a unified deformation model for the markerless capture of multiple scales of human movement, including facial expressions, body motion, and hand gestures. An initial model is generated by locally stitching together models of the individual parts of the human body, which we refer to as the “Frankenstein” model. This model enables the full expression of part movements, including face and hands by a single seamless model. Using a large-scale capture of people wearing everyday clothes, we optimize the Frankenstein model to create “Adam”. Adam is a calibrated model that shares the same skeleton hierarchy as the initial model but can express hair and clothing geometry, making it directly usable for fitting people as they normally appear in everyday life. Finally, we demonstrate the use of these models for total motion tracking, simultaneously capturing the large-scale body movements and the subtle face and hand motion of a social group of people..

Publication

Hanbyul Joo, Tomas Simon, and Yaser Sheikh. Total Capture: A 3D Deformation Model for Tracking Faces, Hands, and Bodies, CVPR, 2018 (Oral). [CVPR Best Student Paper Award]
[pdf] [supplementary]

Dataset

We use the data captured by the Panoptic Studio