Title :
Non-rigid shape and motion recovery: degenerate deformations
Author :
Xiao, Jing ; Kanade, Takeo
Author_Institution :
Robotics Inst., Carnegie Mellon Univ., Pittsburgh, PA, USA
fDate :
27 June-2 July 2004
Abstract :
This paper studies the problem of 3D non-rigid shape and motion recovery from a monocular video sequence, under the degenerate deformations. The shape of a deformable object is regarded as a linear combination of certain shape bases. When the bases are non-degenerate, i.e. of full rank-3, a closed-form solution exists by enforcing linear constraints on both the camera rotation and the shape bases. In practice, degenerate deformations occur often, i.e. some bases are of rank 1 or 2. For example, cars moving or pedestrians walking independently on a straight road refer to rank-1 deformations of the scene. This paper quantitatively shows that, when the shape is composed of only rank-3 and rank-1 bases, i.e. the 3D points either are static or independently move along straight lines, the linear rotation and basis constraints are sufficient to achieve a unique solution. When the shape bases contain rank-2 ones, imposing only the linear constraints results in an ambiguous solution space. In such cases, we propose an alternating linear approach that imposes the positive semi-definite constraint to determine the desired solution in the solution space. The performance of the approach is evaluated quantitatively on synthetic data and qualitatively on real videos.
Keywords :
image motion analysis; image reconstruction; image sequences; video signal processing; 3D nonrigid shape; alternating linear method; camera rotation; cars movement; degenerate deformations; enforcing linear constraints; linear combination; linear rotation; monocular video sequence; motion recovery; pedestrians walk; positive semidefinite constraint; synthetic data; Application software; Cameras; Closed-form solution; Human computer interaction; Layout; Legged locomotion; Roads; Robots; Shape; Video sequences;
Conference_Titel :
Computer Vision and Pattern Recognition, 2004. CVPR 2004. Proceedings of the 2004 IEEE Computer Society Conference on
Print_ISBN :
0-7695-2158-4
DOI :
10.1109/CVPR.2004.1315096