High Resolution Tracking of Non-Rigid Motion of Densely Sampled 3D Data Using Harmonic Maps

Yang Wang, Mohit Gupta, Song Zhang, Sen Wang, Xianfeng Gu, Dimitris Samaras, and Peisen Huang
International Journal of Computer Vision, Vol. 76, No. 3, March, 2008


Download
  • Adobe portable document format (pdf) (2MB)
Copyright notice: This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. These works may not be reposted without the explicit permission of the copyright holder.

Abstract
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 phase-shifting 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.

Keywords
Facial Expression Tracking, Harmonic Maps

Notes

Text Reference
Yang Wang, Mohit Gupta, Song Zhang, Sen Wang, Xianfeng Gu, Dimitris Samaras, and Peisen Huang, "High Resolution Tracking of Non-Rigid Motion of Densely Sampled 3D Data Using Harmonic Maps," International Journal of Computer Vision, Vol. 76, No. 3, March, 2008

BibTeX Reference
@article{Wang_2008_6090,
   author = "Yang Wang and Mohit Gupta and Song Zhang and Sen Wang and Xianfeng Gu and Dimitris Samaras and Peisen Huang",
   title = "High Resolution Tracking of Non-Rigid Motion of Densely Sampled 3D Data Using Harmonic Maps",
   journal = "International Journal of Computer Vision",
   month = "March",
   year = "2008",
   volume = "76",
   number = "3",
}