A joint illumination and shape model for visual tracking

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

Volumn 1, Issue , 2006, Pages 602-609

  Kale, Amit ^a   Jaynes, Christopher ^a  

^a UNIVERSITY OF KENTUCKY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ILLUMINATION MODEL; VIDEO SEQUENCE;

LIGHTING; MATHEMATICAL MODELS; MOTION ESTIMATION; PROBABILITY;

TRACKING (POSITION);

EID: 33845588009     PISSN: 10636919     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CVPR.2006.30     Document Type: Conference Paper

References (13)

1. R. Basri and D. Jacobs. Lambertian reflectance and linear subspaces. IEEE Trans. PAMI, 25(2):218-233, 2003
2. P. Belhumeur and D.J.Kriegman. What is the set of images of an object under all possible illumination conditions. IJCV, 28(3):1-16, 1998
3. B.Han and L. Davis. On-line density-based appearance modeling for object tracking. Proceedings of ICCV, 2005
4. D. Freedman and M. Turek. Illumination-invariant tracking via graph cuts. IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), 2:10-17, 2005
5. W. Freeman and J. Tenenbaum. Learning bilinear models for two factor problems in vision. Proceedings of IEEE CVPR, 1997
6. G. Hager and P. Belhumeur. Efficient region tracking with parametric models of geometry and illumination. IEEE Trans. PAMI, 20(10):1025-1039, 1998
7. M. Isard and A. Blake. Condensation - conditional density propogation for visual tracking. IJCV, 21(1):695-709, 1998
8. A. Kale and C. Jaynes. Shape space sampling distributions and their impact on visual tracking. IEEE International Conference on Image Processing, 2005
9. L. Lu, X.Dai, and G. Hager. A particle filter without dynamics for robust 3d face tracking. Proc. of FPIV, 2004
10. I. Matthews, T. Ishikawa, and S. Baker. The template update problem. In Proceedings of the British Machine Vision Conference, September 2003
11. R. Ramamoorthi. Analytic pea construction for theoretical analysis of lighting variability in images of lambertian object. IEEE Trans. PAMI, 24(10): 1-12, 2002
12. Y. Weiss. Deriving intrinsic images from image sequences. Proc of ICCV, 2001.
13. S. Zhou, R. Chellappa, and B. Moghaddam. Visual tracking and recognition using appearance-adaptive models in particle filters. IEEE Trans. on Image Processing, November 2004.