Supervised learning of edges and object boundaries

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

Volumn 2, Issue , 2006, Pages 1964-1971

  Dollár, Piotr ^a   Tu, Zhuowen ^b   Belongie, Serge ^a  

^a UNIVERSITY OF CALIFORNIA   (United States)

^b UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

BOOSTED EDGE LEARNING; BOUNDARY DETECTION; PROBABILISTIC BOOSTING TREE CLASSIFICATION ALGORITHM; SUPERVISED LEARNING ALGORITHM;

ALGORITHMS; COMPUTER VISION; DECISION MAKING; EDGE DETECTION; PROBABILITY; PROBLEM SOLVING;

LEARNING SYSTEMS;

EID: 33845580709     PISSN: 10636919     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CVPR.2006.298     Document Type: Conference Paper

References (23)

1. K. Branson and S. Belongie, "Tracking Multiple Mouse Contours (without Too Many Samples)", CVPR, 2005.
2. J. F. Canny, "A Computational Approach to Edge Detection", PAMI, Nov. 1986.
3. B. Dubuc and S.W. Zucker, "Complexity, Confusion, and Perceptual Grouping", IJCV, 2001.
4. Y. Freund and R. Schapire, "A Decision-theoretic Generalization of On-line Learning And an Application to Boosting", ICML, 1996.
5. J. Friedman, T. Hastie and R. Tibshirani, "Additive logistic regression: a statistical view of boosting", Stanford Tech Report. 1998.
6. D. Geman and B. Jedynak, "An Active Testing Model for Tracking Roads in Satellite Images", PAMI, 1996.
7. B. Geisler, "Perceptual Grouping and the Bayesian Statistics of Natural Scenes," Bayes, San Francisco, 2001.
8. C.E. Guo, S.C. Zhu, and Y.N. Wu, "A mathematical theory of primal sketch and sketchability", ICCV, 2003.
9. A. Hertzmann, C. Jacobs, N. Oliver, B. Curless, D. Salesin. "Image Analogies", SIGGRAPH, 2001
10. D. Marr, "Vision", 1982.
11. D. Martin, C. Fowlkes, & J. Malik, "Learning to Detect Natural Image Boundaries Using Local Brightness, Color and Texture Cues", PAMI04.
12. K. Koffka, "Principles of Gestalt Psychology", New York: Harcourt, Brace and company 1935.
13. S. Konishi, A. Yuille, J. Coughlan and S.C. Zhu, "Statistical Edge Detection: Learning and Evaluating Edge Cues", PAMI, Jan, 2003.
14. V. Ramesh, "Performance Characterization of Image Understanding Algorithms", Ph.D. thesis, University of Washington.
15. X. Ren, C. Fowlkes, and J. Malik, "Scale-Invariant Contour Completion using Conditional Random Fields", ICCV, 2005.
16. M. Singh. "Modal and Amodal Completion Generate Different Shapes", Psychological Science, 2004.
17. J. Sullivan and S. Carlsson "Recognizing and Tracking Human Action", ECCV, 2002.
18. C. Taylor and D. Kriegman, "Structure and Motion from Line Segments in Multiple Images", PAMI, 1995.
19. Z. Tu, X. Chen, A. Yuille and S.C. Zhu, "Image Parsing: Unifying Segmentation, Detection, and Object Recognition", IJCV, 2005.
20. Z. Tu, "Probabilistic Boosting-Tree: Learning Discriminative Models for Classification, Recognition, and Clustering", ICCV05.
21. S. Ullman R. Basri "Recognition by Linear Combinations of Models", PAMI, May, 1991.
22. P. Viola and M. Jones, "Robust Real Time Object Detection", SCTV, 2001.
23. L.R. Williams and D.W. Jacobs, "Stochastic Completion Fields: A Neural Model of Illusory Contour Shape and Salience", Neural Computation, 1997.