Pose estimation from video sequences based on sylvester's equation

Proceedings of SPIE - The International Society for Optical Engineering

Volumn 6508, Issue PART 2, 2007, Pages

  Chen, Chong ^c   Schonfeld, Dan ^c   Yang, Junlan ^a   Mohamed, Magdi ^b  

^a 1120 Science and Engineering Offices   (United States)

^b MOTOROLA INC   (United States)

^c NONE

Author keywords

Lagrange multiplier; Particle filtering; Pose estimation; Sylvester's equation

Indexed keywords

FEATURE EXTRACTION; IMAGE ANALYSIS; LAGRANGE MULTIPLIERS; OPTICAL FILTERS; SINGULAR VALUE DECOMPOSITION;

PARTICLE FILTERING; POSE ESTIMATION; SYLVESTER'S EQUATION; VIDEO SEQUENCES;

MOTION ESTIMATION;

EID: 35148830268     PISSN: 0277786X     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1117/12.702601     Document Type: Conference Paper

References (16)

1. S. O. Ba and J. M. Odobez, "A probabilistic framework for joint head tracking and pose estimation," in Proceedings of 17th International Conference Pattern Recognition, 4, pp. 264-267, 2004.
2. K. S. Arun, T. S. Huang, and S. D. Rlostein, "Least-squares fitting of two 3-d point sets," IEEE Trunsactions on Pattern Analysis and Machine Intelligence 9(5), pp. 698-700, 1987.
3. M. S. Arulampalam, S. Maskell, N. Gordon, and T. Clapp, "A tutorial on particle filters for. online nonlinear/nongaussian bayesian tracking," IEEE Transactions Signal Processing 50(2), pp. 174-188, 2002.
4. M. Isard and A. Blake, "Contour tracking by stochastic propagation of conditional density," in Proceedings European Conference on Computer Vision, pp. 343-356, 1996.
5. N. Bouaynaya and D. Schonfeld, "Complete system for head tracking using motion-based particle filter and randomly perturbed active contour," in Proceedings of SPIE, Image and Video Communications and Processing (IVCP'05), 5685, pp. 864-873, 2005.
6. K. Nummiaroa, E. K. Meierb, and L. V. Gool, "An adaptive color-based particle filter," Image and Vision Computing 21(11), pp. 99-110, 2002.
7. D. G. Lowe, "Distinctive image features from scale-invariant keypoints," International Journal of Computer Vision 60(2), pp. 91-110, 2004.
8. M. A. Fischler and R. C. Bolles, "Random sample consensus: A paradigm for model fitting with applications to image analysis and automated cartography," Communication of the ACM 24(6), pp. 381-395, 1981.
9. A. A. T. Jebara and A. Pentland, "3d structure from 2d motion," IEEE Signal Processing Magazine 16(3), pp. 66-84, 1999.
10. S. S. H. Adams and D. Strelow, "An empirical comparison of methods for image-based motion estimation," in IEEE/RSJ International Conference on Intelligent Robots and System, 1, pp. 123-128, 2002.
11. Q. Ji, "3d face pose estimation and tracking from a monocular camera," in Image and Vision Computing, 2002.
12. R. M. Haralick, C.-N. L. H. Joo, V. G. V. X. Zhuang, and M. B. Kim, "Pose estimation from corresponding point data," IEEE Trunsactions on Systems, Man and Cybernetics 19(6), pp. 698-700, 1989.
13. C. F. V. Loan, "The ubiquitous kronecker product," Journal of Computational and Applied Mathematics 123, pp. 85-100, 2000.
14. N. J. Higham, "Perturbation theory and backward error for ax+xb=c," in Numerical Analysis Report No. 211, University of Manchester, 1992.
15. S. O. Ba and J. M. Odobez, "Evaluation of multiple cues head pose tracking algorithm in indoor environments," in Proceedings of International Conference on Multimedia and Expo, ICME 2005, 2005.
16. "Pointing'04 icpr workshop: Head pose image database," in http://www-prima.inrialpes.fr/Pointing04/dataface.html, 2004.