A closed-form solution to non-rigid shape and motion recovery

International Journal of Computer Vision

Volumn 67, Issue 2, 2006, Pages 233-246

  Xiao, Jing ^a   Chai, Jinxiang ^b   Kanade, Takeo ^b  

^a Epson Palo Alto Laboratory   (United States)

^b CARNEGIE MELLON UNIVERSITY   (United States)

Author keywords

Ambiguity; Basis constraints; Closed form solution; Non rigid structure from motion; Rotation constraint; Shape bases

Indexed keywords

COMPUTER VISION; CONSTRAINT THEORY; HUMAN COMPUTER INTERACTION; IMAGE PROCESSING; MATHEMATICAL TRANSFORMATIONS; PATTERN RECOGNITION;

CLOSED-FORM SOLUTION; NON-RIGID STRUCTURE FROM MOTION; ROTATION CONSTRAINT;

MOTION ESTIMATION;

EID: 33646511094     PISSN: 09205691     EISSN: 15731405     Source Type: Journal    
DOI: 10.1007/s11263-005-3962-9     Document Type: Conference Paper

References (25)

1. Baker, S. and Matthews, I. 2001. Equivalence and efficiency of image alignment algorithms. In Proc. Int. Conf. Computer Vision and Pattern Recognition.
2. Bascle, B. and Blake, A. 1998. Separability of pose and expression in facial tracing and animation. In Proc. Int. Conf. Computer Vision, pp. 323-328.
3. Blanz, V. and Vetter, T. 1999. A morphable model for the synthesis of 3D faces. In P roc. SIGGRAPH'99, pp. 187-194.
4. Brand, M. 2001. Morphable 3D models from video. In Proc. Int. Conf. Computer Vision and Pattern Recognition.
5. Brand, M. and Bhotika, R. 2001. Flexible flow for 3D nonrigid tracking and shape recovery. In Proc. Int. Conf. Computer Vision and Pattern Recognition.
6. Bregler, C., Hertzmann, A. and Biermann, H. 2000. Recovering non-rigid 3D shape from image streams. In Proc. Int. Conf. Computer Vision and Pattern Recognition.
7. Chai, J., Xiao, J., and Hodgins, J. 2003. Vision-based control of 3D facial animation. Eurographics/ACM Symposium on Computer Animation.
8. Costeira, J. and Kanade, T. 1998. A multibody factorization method for independently moving-objects. Int. Journal of Computer Vision, 29(3):159-179.
9. Gokturk, S.B., Bouguet, J.Y., and Grzeszczuk, R. 2001. A data driven model for monocular face tracking. In Proc. Int. Conf. Computer Vision.
10. Han, M. and Kanade, T. 2000. Reconstruction of a scene with multiple linearly moving objects. In Proc. Int. Conf. Computer Vision and Pattern Recognition.
11. Hartley, R. I. and Zisserman, A. 2000. Multiple View Geometry in Computer Vision. Cambridge University Press.
12. Kanatani, K. 2001. Motion segmentation by subspace separation and model selection. In Proc. Int. Conf. Computer Vision.
13. Mahamud, S. and Hebert, M. 2000. Iterative projective reconstruction from multiple views. In Proc. Int. Conf. Computer Vision and Pattern Recognition.
14. Poelman, C. and Kanade, T. 1997. A paraperspective factorization method for shape and motion recovery, IEEE Trans. Pattern Analysis and Machine Intelligence, 19(3):206-218.
15. Schönemann, P.H. 1966. A generalized solution of the orthogonal procrustes problem. Psychometrika, 31(1):1-10.
16. Sugaya, Y. and Kanatani, K. 2004. Geometric structure of degeneracy for multi-body motion segmentation. ECCV Workshop on Statistical Methods in Video Processing.
17. Tomasi, C. and Kanade, T. 1992. Shape and motion from image streams under orthography: A factorization method. Int. Journal of Computer Vision, 9(2): 137-154.
18. Torresani, L., Yang, D., Alexander, G., and Bregler, C. 2001. Tracking and modeling non-rigid objects with rank constraints. In Proc. Int. Conf. Computer Vision and Pattern Recognition.
19. Triggs, B. 1996. Factorization methods for projective structure and motion. In Proc. Int. Conf. Computer Vision and Pattern Recognition.
20. Vidal, R., Soatto, S., Ma, Y., and Sastry, S. 2002. Segmentation of dynamic scenes from the multibody fundamental matrix. ECCV Workshop on Vision and Modeling of Dynamic Scenes.
21. Vidal, R. and Hartley, R. 2004. Motion segmentation with missing data using power factorization and GPCA. In Proc. Int. Conf. Computer Vision and Pattern Recognition.
22. Wolf, L. and Shashua, A. 2001. Two-body segmentation from two perspective views. In Proc. Int. Conf. Computer Vision and Pattern Recognition.
23. 2,κ = 3,...,6, and their applications in computer vision. Int. J. of Computer Vision, 48(1):53-67.
24. Zelnik-Manor, L. and Irani, M. 2003. Degeneracies, dependencies, and their implications in multi-body and multi-sequence factorizations. In Proc. Int. Conf. Computer Vision and Pattern Recognition.
25. Zhang, Z., Deriche, R., Faugeras, O., and Luong, Q. 1995. A robust technique for matching two uncalibrated images through the recovery of the unknown epipolar geometry, Artificial Intelligence, 78(1/2):87-119.