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15th International Conference on Pattern Recognition (ICPR'00) - Volume 3
Framework of Integrating 2D Points and Curves for Tracking of 3D Nonrigid Motion and Structure
Barcelona, Spain
September 03-September 08
ISBN: 0-7695-0750-6
ASCII Text
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Min C. Shin, Ramprasad Balasubramanian, Dmitry Goldgof, Carlos Kim, "Framework of Integrating 2D Points and Curves for Tracking of 3D Nonrigid Motion and Structure," Pattern Recognition, International Conference on, vol. 3, pp. 3831, 15th International Conference on Pattern Recognition (ICPR'00) - Volume 3, 2000.
 
 
BibTex
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@article{ 10.1109/ICPR.2000.903671,
author = {Min C. Shin and Ramprasad Balasubramanian and Dmitry Goldgof and Carlos Kim},
title = {Framework of Integrating 2D Points and Curves for Tracking of 3D Nonrigid Motion and Structure},
journal ={Pattern Recognition, International Conference on},
volume = {3},
year = {2000},
isbn = {0-7695-0750-6},
pages = {3831},
doi = {http://doi.ieeecomputersociety.org/10.1109/ICPR.2000.903671},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - CONF
JO - Pattern Recognition, International Conference on
TI - Framework of Integrating 2D Points and Curves for Tracking of 3D Nonrigid Motion and Structure
SN - 0-7695-0750-6
SP
EP
A1 - Min C. Shin,
A1 - Ramprasad Balasubramanian,
A1 - Dmitry Goldgof,
A1 - Carlos Kim,
PY - 2000
VL - 3
JA - Pattern Recognition, International Conference on
ER -
 
Min C. Shin, University of South Florida
Ramprasad Balasubramanian, University of South Florida
Dmitry Goldgof, University of South Florida
Carlos Kim, University of South Florida
In this paper, we present a method for 3D non-rigid motion tracking and structure reconstruction from 2D points and curve segments from a sequence of perspective images. The 3D locations of features in the first frame are known. The 3D affine motion model is used to describe the non-rigid motion. The results from synthetic and real data are presented. The applications include lip tracking, MPEG4 face player, and burn scar assessment. The results show (1) curve segments are more robust under noise (observed from synthetic data with different Gaussian noise level), and (2) using both feature yields a significant performance gain in real data.
Citation:
Min C. Shin, Ramprasad Balasubramanian, Dmitry Goldgof, Carlos Kim, "Framework of Integrating 2D Points and Curves for Tracking of 3D Nonrigid Motion and Structure," icpr, vol. 3, pp.3831, 15th International Conference on Pattern Recognition (ICPR'00) - Volume 3, 2000
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