Building robust appearance models using on-line feature selection

Proceedings of SPIE - The International Society for Optical Engineering

Volumn 6574, Issue , 2007, Pages

  Porter, R ^a   Loveland, R ^a   Rosten, E ^a  

^a LOS ALAMOS NATIONAL LABORATORY   (United States)

Author keywords

Adaptive appearance models; Feature selection; Recognition; Tracking

Indexed keywords

COMPUTATIONAL METHODS; MATHEMATICAL MODELS; ONLINE SYSTEMS; OPTIMIZATION; PROBLEM SOLVING; TRACKING (POSITION);

ADAPTIVE APPEARANCE MODELS; ONLINE FEATURE SELECTION; ROBUST APPEARANCE MODELS; TARGET APPEARANCE MODELS;

FEATURE EXTRACTION;

EID: 36148957566     PISSN: 0277786X     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1117/12.721439     Document Type: Conference Paper

References (14)

1. S. Baker and I. Matthews. "Lucas-kanade 20 years on: A unifying framework.", International Journal of Computer Vision, 56(3), 221-255, (2004).
2. B. D. Lucas and T. Kanade. "An iterative image registration technique with application to stereo vision.", 7th International Joint Conference on Artificial Intelligence, 674-679, (1981).
3. J.R. Bergen, P. Anandan, K.J. Hanna, and R. Hingorani. "Hierarchical model-based motion estimation.", Proc. of ECCV, 237-252, (1992).
4. G. Hager and P. Belhumeur. "Efficient region tracking with parametric models of geometry and illumination", IEEE Trans Pattern Analysis and Machine Intelligence, 20(10), 1025-1039, (1998).
5. M. Black and A. Jepson. "Eigen-tracking: Robust matching and tracking of articulated objects using a view-based representation", Proc. of ECCV, 329-342, (1998).
6. I. Matthews and T. Ishikawa and S. Baker. "The template update problem", IEEE Transactions on Pattern Analysis and Machine Intelligence, 26(6), 810-815, (2003).
7. Kuang-Chih Lee and David Kriegman, " Online learning of probabilistic appearance manifolds for video-based recognition and tracking ", Proc. CVPR, 852-859, (2005).
8. Allan D. Jepson, David J. Fleet and Thomas F. El-maraghi, "Robust Online Appearance Models for Visual Tracking", Proc. CVPR, 415-422 (2001).
9. R. T. Collins, Y.X. Liu, and M. Leordeanu, "Online selection of discriminative tracking features", IEEE Transactions on Pattern Analysis and Machine Intelligence, 27(10), 1631-43 (2005).
10. Lawrence D. Stone, Carl A. Barlow and Thomas L. Corwin, Bayesian Multiple Target Tracking, Artech House, Boston, 1999.
11. Michael Isard and Andrew Blake, "CONDENSATION - conditional density propagation for visual tracking", Int. J. Computer Vision 29(1), 5-28, (1998).
12. P. Th'evenaz, U.E. Ruttimann, and M. Unser, "A pyramid approach to subpixel registration based on intensity", IEEE Transactions on Image Processing, 7(1), 27-41, (1998).
13. Y.Freund, and R.E. Schapire. "Decision-theoretic generalization of on-line learning and an application to boosting", Journal of Computer and System Sciences, 55(1), 119-139, (1997).
14. K. Glocer, D. Eads, and J. Theiler. "Online Feature Selection for Pixel Classification.", Proc. ICML 22, 249-256 (2005).