Group action induced distances for averaging and clustering linear dynamical systems with applications to the analysis of dynamic scenes

Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition

Volumn , Issue , 2012, Pages 2208-2215

  Afsari, Bijan ^a   Chaudhry, Rizwan ^a   Ravichandran, Avinash ^b   Vidal, Rene ^a  

^a Johns Hopkins University   (United States)

^b UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CLASSIFICATION AND CLUSTERING; DYNAMIC SCENES; DYNAMIC VISUAL SCENES; GROUP ACTIONS; HIGH-DIMENSIONAL; LARGE-SCALE PROBLEM; LINEAR DYNAMICAL SYSTEMS; NON-EUCLIDEAN; ORTHOGONAL MATRIX; STATE SPACE REALIZATION; STATE-OF-THE-ART METHODS; TIME-SERIES DATA;

LINEAR CONTROL SYSTEMS; MATRIX ALGEBRA;

COMPUTER VISION;

EID: 84866687845     PISSN: 10636919     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CVPR.2012.6247929     Document Type: Conference Paper

References (23)

1. P.-A. Absil, R. Mahony, and R. Sepulchre. Optimization Algorithms on Matrix Manifolds. Princeton University Press, Princeton, NJ, 2008.
2. R. Bhattacharya and V. Patrangenaru. Large sample theory of intrinsic and extrinsic sample means on manifolds. I. Ann. Statist., 2003.
3. A. Bissacco, A. Chiuso, Y. Ma, and S. Soatto. Recognition of human gaits. In CVPR, 2001.
4. A. Chan and N. Vasconcelos. Probabilistic kernels for the classification of auto-regressive visual processes. In CVPR, 2005.
5. A. Chan and N. Vasconcelos. Classifying video with kernel dynamic textures. In CVPR, 2007.
6. A. Chan and N. Vasconcelos. Layered dynamic textures. TPAMI, 2009.
7. R. Chaudhry and Y. Ivanov. Fast approximate nearest neighbor methods for non-euclidean manifolds with applications to human activity analysis in videos. In ECCV, 2010.
8. R. Chaudhry, A. Ravichandran, G. Hager, and R. Vidal. Histograms of oriented optical flow and Binet-Cauchy kernels on nonlinear dynamical systems for the recognition of human actions. In CVPR, 2009.
9. R. Chaudhry and R. Vidal. Recognition of visual dynamical processes: Theory, kernels and experimental evaluation. TR 09-01, Dept. CS, JHU, 2009.
10. K. D. Cock and B. D. Moor. Subspace angles and distances between ARMA models. System and Control Letters, 2002.
11. G. Doretto, A. Chiuso, Y. Wu, and S. Soatto. Dynamic textures. IJCV, 2003.
12. A. Edelman, T. Arias, and S. T. Smith. The geometry of algorithms with orthogonality constraints. SIAM J Mat. Anal.App., 1998.
13. L. Gorelick, M. Blank, E. Shechtman, M. Irani, and R. Basri. Actions as space-time shapes. TPAMI, 2007.
14. B. Hanzon. Identifiability, Recursive Identification and Spaces of Linear Dynamical Systems, volume CWI Tracts 63 and 64. Centrum voor Wiskunde en Informatica (CWI), Amsterdam, 1989.
15. J. M. Lee. Introduction to Smooth Manifolds. Graduate Texts in Mathematics. Springer, 2002.
16. A. Martin. A metric for ARMA processes. TSP, 2000.
17. A. Ravichandran, R. Chaudhry, and R. Vidal. View-invariant dynamic texture recognition using a bag of dynamical systems. In CVPR, 2009.
18. A. Ravichandran, P. Favaro, and R. Vidal. A unified approach to segmentation and categorization of dynamic textures. In ACCV, 2010.
19. A. Ravichandran and R. Vidal. Video registration using dynamic textures. In ECCV, 2008.
20. P. Saisan, A. Bissacco, A. Chiuso, and S. Soatto. Modeling and synthesis of facial motion driven by speech. In ECCV, 2004.
21. P. Turaga, A. Veeraraghavan, and R. Chellappa. Statistical analysis on Stiefel and Grassmann manifolds with applications in computer vision. In CVPR, 2008.
22. S. Vishwanathan, A. Smola, and R. Vidal. Binet-Cauchy kernels on dynamical systems and its application to the analysis of dynamic scenes. IJCV, 2007.
23. L. Younes. Shapes and Diffeomorphisms, vol. 171 App. Mathematical Sciences. Springer, 2010.