Exploring face space

IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops

Volumn 2004-January, Issue January, 2004, Pages

  Sim, Terence ^a   Zhang, Sheng ^a  

^a NATIONAL UNIVERSITY OF SINGAPORE   (Singapore)

Author keywords

face recognition; face space; pattern recognition

Indexed keywords

PROBABILITY DENSITY FUNCTION;

BAYES CLASSIFIER; CLUSTER BOUNDARIES; FACE IMAGES; FACE SPACE; INTER CLASS; INTRA CLASS; K-MEANS++ CLUSTERING; ROBUST SOLUTIONS; STILL-IMAGES; VIEWING CONDITIONS;

FACE RECOGNITION;

EID: 84932642472     PISSN: 21607508     EISSN: 21607516     Source Type: Conference Proceeding    
DOI: 10.1109/CVPR.2004.337     Document Type: Conference Paper

References (16)

1. Y. Adini, Y. Moses, and S. Ullman. Face Recognition: The Problem of Compensating for Changes in Illumination Direction. IEEE Transactions on Pattern Analysis and Machine Intelligence, 19(7):721-732, 1997.
2. P. Belhumeur,J. Hespanha,D. Kriegman. Eigenfaces vs. Fisherfaces: Recognition Using Class Specific Linear Projection. IEEE Transactions on Pattern Analysis and Machine Intelligence 19 7, 1997.
3. R. Brunelli and T. Poggio. Face recognition: Features versus templates. IEEE Transactions on Pattern Analysis and Machine Intelligence, 15(10), 1993.
4. J. Daugman. Face and Gesture Recognition: Overview. IEEE Transactions on Pattern Analysis and Machine Intelligence, 19(7):675-676, 1997.
5. R. Duda, P. Hart, and D. Stork. Pattern Classification, 2nd edition. John Wiley and Sons, 2000.
6. J. Foley, A. Van Dam, S. Feiner, and J. Hughes. Computer Graphics: Principles and Practice. Addison Wesley, 1993.
7. A.S. Georghiades, P.N. Belhumeur, and D.J. Kriegman. From Few to Many: Generative Models for Recognition Under Variable Pose and Illumination. In IEEE International Conference on Automatic Face and Gesture Recognition, 2000.
8. M. Kirby and L. Sirovich. Application of the Karhunen-Loeve Procedure for the Characterization of Human Faces. IEEE Trans. Pattern Anal. Mach. Intell., 12(1):103-108, 1990.
9. D. MacKay. Introduction to Monte Carlo Methods, in Learning in Graphical Models. MIT Press, 1999.
10. P. Phillips, P. Grother, R. Micheals, and D. Blackburn. Facial Recognition Vendor Test 2002. http://www.frvt. org.
11. T. Sim and T. Kanade. Combining Models and Exemplars for Face Recognition: An Illuminating Example. In Workshop on Models versus Exemplars in Computer Vision, Computer Vision Pattern Recognition Conference, 2001.
12. S. Sudeep. Human ID Project at University of South Florida, 2001. http://marathon.csee.usf.edu/HumanID/index.html.
13. J. B. Tenenbaum, V. De Silva, and J. C. Langford. A Global Geometric Framework for Nonlinear Dimensionality Reduction. Science, 290:2319-2323, 2000.
14. M. Turk and A. Pentland. Eigenfaces for Recogn ition. Journal of Cognitive Neuroscience, 3(1), 1991.
15. N. Vlassis and A. Likas. A Greedy EM Algorithm for Gaussian Mixture Learning. Neural Processing Letters, 15(1):77-87, February 2002.
16. W. Zhao and R. Chellappa and A. Rosenfeld and P. Phillips. Face recognition: A literature survey. Technical Report CAR-TR-948, Center for Automation Research, University of Maryland, 2000.