DocumentCode
3407425
Title
Model evolution: An incremental approach to non-rigid structure from motion
Author
Zhu, Shengqi ; Zhang, Li ; Smith, Brandon M.
Author_Institution
Univ. of Wisconsin-Madison, Madison, WI, USA
fYear
2010
fDate
13-18 June 2010
Firstpage
1165
Lastpage
1172
Abstract
In this paper, we present a new framework for non-rigid structure from motion (NRSFM) that simultaneously addresses three significant challenges: severe occlusion, perspective camera projection, and large non-linear deformation. We introduce a concept called a model graph, which greatly reduces the computational cost of discovering groups of input images that depict consistent 3D shapes. A 3D model is constructed for each input image by traversing the model graph along multiple evolutionary paths. A compressive shape representation is constructed, which (1) consolidates the multiple 3D models for each image reconstructed during model evolution and (2) reduces the number of models needed to represent the input image set. Assuming feature correspondences are known, we demonstrate our algorithm on both real and synthetic data sets that exemplify all three aforementioned challenges.
Keywords
computer graphics; image motion analysis; image representation; 3D model; compressive shape representation; consistent 3D shapes; input image set represention; large nonlinear deformation; model evolution; multiple evolutionary paths; nonrigid structure from motion; perspective camera projection; severe occlusion; Cameras; Computational efficiency; Computer vision; Deformable models; Face; Image coding; Image reconstruction; Large-scale systems; Robustness; Shape;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Vision and Pattern Recognition (CVPR), 2010 IEEE Conference on
Conference_Location
San Francisco, CA
ISSN
1063-6919
Print_ISBN
978-1-4244-6984-0
Type
conf
DOI
10.1109/CVPR.2010.5540085
Filename
5540085
Link To Document