A novel approach for person authentication and content-based tracking in videos using kernel methods and active appearance models

Proceedings of the IEEE International Conference on Systems, Man and Cybernetics

Volumn 2, Issue , 2003, Pages 1384-1389

  Kumar, Nimit ^a   Abhishek, Vibhanshu ^a   Gautam, Gagan ^a  

^a INDIAN INSTITUTE OF TECHNOLOGY KANPUR   (India)

Author keywords

Active appearance models; ICA; Information theory; Kernel based learning; Mean shift tracking; SVM

Indexed keywords

COLOR IMAGE PROCESSING; CONTENT BASED RETRIEVAL; FEATURE EXTRACTION; IMAGE ANALYSIS; IMAGE SEGMENTATION; LEARNING ALGORITHMS; REAL TIME SYSTEMS;

ACTIVE APPEARANCE MODEL; CONTENT-BASED TRACKING; FACE DETECTION; KERNEL-BASED LEARNING ALGORITHM; PERSON AUTHETICATION; REAL TIME SECURITY SYSTEM; SKIN-COLOR SEGMENTATION;

FACE RECOGNITION;

EID: 0242492081     PISSN: 08843627     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (14)

1. M. S. Bartlett, J. R. Movellan, and T. J. Sejnowski, "Face Recognition using Independent Component Analysis," IEEE Trans. on Neural Networks, Vol 13, No. 6, pp. 1450-1464, Nov. 2002.
2. D. Comaniciu, V. Ramesh, and P. Meer, "Kernel-Based Object Tracking," IEEE Trans. on Pattern Analysis and Machine Intelligence, Vol 25, No. 5, pp. 564-577, May 2003.
3. D. Comaniciu and P. Meer, "Mean Shift: A Robust Approach Towards Feature Space Analysis," IEEE Trans. on Pattern Analysis and Machine Intelligence, Vol 24, No. 5, pp. 603-619, May 2002.
4. T. F. Cootes, G. J. Edwards, and C. J. Taylor, "Active Appearance Models," in Proceedings of European Conf. on Computer-Vision, Vol 2, pp. 484-498, Springer, 1998.
5. N. Cristianini and J. Shawe-Taylor, An Introduction to Support Vector Machines and Other Kernel-Based Learning Methods, Cambridge University Press, 2000.
6. G. J. Edwards, C. J. Taylor, and T. F. Cootes, "Interpreting Face Images using Active Appearance Models," in Proceedings of Third IEEE Intl. Conf. on Automatic Face and Gesture Recognition, pp. 300-305, 1998.
7. T. Kailath, "The divergence and Bhattacharya distance measures in signal selection," IEEE Trans. on Communication Technology, Vol 15, pp. 52-60, 1967.
8. M. S. Lew and N. Huijsmans, "Information Theory and Face Detection," Proceedings of 13th Intl. Conf. on Pattern Recognition, Vol 3, pp. 601-605, Aug, 1996.
9. S. Z. Li., Q. Fu, L. Gu, B. Scholkopf, Y. Cheng, H. Zhang, "Kernel machine based learning for multi-view face detection and pose estimation," in Proceedings of Eighth IEEE Intl. Conf. on Computer Vision, Vol 2, pp. 674-679, July 2001.
10. Y. Li, S. Gong, J. Sherrah, and H. Liddell, "Multi-view face detection using support vector machines and eigenspace modeling," in Proceedings of Fourth Intl. Conf. on Knowledge-based Intelligent Engineering Systems and Allied Technologies, Vol 1, pp. 241-244, 2000.
11. H. Rowley, S. Baluja, and T. Kanade, "Neural-network based face detection," IEEE Trans. on Pattern Analysis and Machine Intelligence, Vol 20. No. 1, pp. 23-38, Jan. 1998.
12. R. Sukthankar and R. Stockton, "Argus: The Digital Doorman", IEEE Intelligent Systems, Vol 16, No. 2, pp. 14-19, March-April, 2001.
13. V. N. Vapnik, Statistical Learning Theory, John Wiley and Sons, Inc., New York, 1998.
14. CMU Face Database available at http://vasc.ri.cmu.edu/idb/html/face/index.html