High Resollution Tracking of Non-Rigid Motion of Densely Sampled 3D Data Using Harmonic Maps
International Journal of Computer Vision
Yang Wang, Mohit Gupta, Song Zhang, Sen Wang, Xianfeng Gu, Dimitris Samaras and Peisen Huang
We present a novel automatic method for high resolution, non-rigid dense 3D point tracking. High
quality dense point clouds of non-rigid geometry moving at video speeds are acquired using a phaseshifting
structured light ranging technique. To use such data for the temporal study of subtle motions
such as those seen in facial expressions, an efficient non-rigid 3D motion tracking algorithm is needed
to establish inter-frame correspondences. The novelty of this paper is the development of an algorithmic
framework for 3D tracking that unifies tracking of intensity and geometric features, using harmonic maps
with added feature correspondence constraints. While the previous uses of harmonic maps provided
only global alignment, the proposed introduction of interior feature constraints allows to track non-rigid
deformations accurately as well. The harmonic map between two topological disks is a diffeomorphism
with minimal stretching energy and bounded angle distortion. The map is stable, insensitive to resolution
changes and is robust to noise. Due to the strong implicit and explicit smoothness constraints imposed
by the algorithm and the high-resolution data, the resulting registration/deformation field is smooth,
continuous and gives dense one-to-one inter-frame correspondences. Our method is validated through a
series of experiments demonstrating its accuracy and efficiency.