DocumentCode :
3003714
Title :
Linear embeddings in non-rigid structure from motion
Author :
Rabaud, Vincent ; Belongie, Serge
Author_Institution :
Dept. of Comput. Sci. & Eng., Univ. of California, San Diego, CA, USA
fYear :
2009
fDate :
20-25 June 2009
Firstpage :
2427
Lastpage :
2434
Abstract :
This paper proposes a method to recover the embedding of the possible shapes assumed by a deforming nonrigid object by comparing triplets of frames from an orthographic video sequence. We assume that we are given features tracked with no occlusions and no outliers but possible noise, an orthographic camera and that any 3D shape of a deforming object is a linear combination of several canonical shapes. By exploiting any repetition in the object motion and defining an ordering between triplets of frames in a generalized non-metric multi-dimensional scaling framework, our approach recovers the shape coefficients of the linear combination, independently from other structure and motion parameters. From this point, a good estimate of the remaining unknowns is obtained for a final optimization to perform full non-rigid structure from motion. Results are presented on synthetic and real image sequences and our method is found to perform better than current state of the art.
Keywords :
image sequences; video signal processing; 3D shape; canonical shapes; deforming nonrigid object; feature tracking; generalized nonmetric multidimensional scaling framework; image sequences; linear embeddings; motion parameters; nonrigid structure; orthographic camera; orthographic video sequence; shape coefficients; Cameras; Geometry; Image reconstruction; Nonlinear distortion; Optical distortion; Optical reflection; Optical refraction; Robustness; Surface reconstruction; Utility programs;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Vision and Pattern Recognition, 2009. CVPR 2009. IEEE Conference on
Conference_Location :
Miami, FL
ISSN :
1063-6919
Print_ISBN :
978-1-4244-3992-8
Type :
conf
DOI :
10.1109/CVPR.2009.5206628
Filename :
5206628
Link To Document :
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