Novel likelihood estimation technique based on boosting detector

Proceedings - International Conference on Image Processing, ICIP

Volumn 3, Issue , 2005, Pages 477-480

  Wang, Haijing ^a,b   Li, Peihua ^c   Zhang, Tianwen ^b  

^a IEEE   (China)

^b HARBIN INSTITUTE OF TECHNOLOGY   (China)

^c HEILONGJIANG UNIVERSITY   (China)

Author keywords

[No Author keywords available]

Indexed keywords

BOOSTING DETECTORS; GENTLE ADABOOST (GAB); PROBABILITY INTRA STAGE (PIS); PROBABILITY OUTER STAGE (POS);

CLASSIFICATION (OF INFORMATION); FUNCTIONS; MAXIMUM LIKELIHOOD ESTIMATION; PROBABILITY; TRACKING (POSITION);

OBJECT RECOGNITION;

EID: 33744903509     PISSN: 15224880     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICIP.2005.1530432     Document Type: Conference Paper

References (10)

1. M.-.H Yang, D. J. Kriegman, and N. Ahuja "Detecting faces in images: A survey," IEEE Trans. on Pattern Analysis and Machine Intelligence, vol. 24, no. 1, pp. 34-58, 2002.
2. K. Okuma, A. Taleghani, N. D. Freitas, J. J. Little, and D. G. Lowe, "A boosted particle filter: Multitarget detection and tracking," in ECCV, 2004, pp. 28-39.
3. A. Treptow, A. Masselli, and A. Zell, "Real-time object tracking for soccer-robots without color information," in European Conference on Mobile Robots, 2003.
4. P. Li and H. Wang, "Probabilistic face tracking using boosted mult-view detector," in IEEE Pacific-Rim on Multimedia, Tokyo WaterFront City, Japan, Nov. 2004.
5. P. Li, T. Zhang, and A.E.C. Pece, "Visual contour tracking based on particle filters," Image and Vision Computing, vol. 21, no. 1, pp. 111-123, 2003.
6. Y. Freund and R. E. Schapire, "A decision-theoretic generalization of on-line learning and an application to boosting," in European Conference on Computational Learning Theory, 1995, pp. 23-37.
7. P. Viola and M. Jones, "Robust real-time object detection," in Second International Workshop on Statistical and Computational Theories of Vision - Modeling, Learning, Computing, and Sampling, Vancouver, Canada, Jul. 2001.
8. J. Friedman, T. Hastie, and R. Tibshirani, "Additive logistic regression: a statistical view of boosting," Technical report, Department of Statistics, Stanford University, 1998.
9. Y. Freund and R. E. Schapire, "Experiments with a new boosting algorithm," in Machine Learning: Proceedings of the Thirteenth International Conference, Morgan Kauffman, San Francisco, 1996, pp. 148-156.
10. R. E. Schapire and Y. Singer, "Improved boosting algorithms using confidence-rated predictions," Machine Learning, vol. 37, pp. 297-336, 1999.