Face detection using mixtures of linear subspaces

Proceedings - 4th IEEE International Conference on Automatic Face and Gesture Recognition, FG 2000

Volumn , Issue , 2000, Pages 70-76

  Yang, Ming Hsuan ^a   Ahuja, Narendra ^a   Kriegman, David ^a  

^a University of Illinois at Urbana Champaign   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; CONFORMAL MAPPING; FACE RECOGNITION; MAXIMUM LIKELIHOOD ESTIMATION;

DIMENSIONALITY REDUCTION; FISHER LINEAR DISCRIMINANTS; GRAY LEVEL IMAGE; LIGHTING CONDITIONS; LINEAR SUBSPACE; MAXIMUM LIKELIHOOD ESTIMATE; MIXTURE OF FACTOR ANALYZERS; MIXTURE OF SUBSPACES;

MIXTURES;

EID: 33745137045     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/AFGR.2000.840614     Document Type: Conference Paper

References (23)

1. T. W. Anderson An Introduction to Multivariate Statistical Analysis. John Wiley New York 1984.
2. P. Belhumeur J. Hespanha and D. Kriegman. Eigenfaces vs. fisherfaces: Recognition using class specific linear projection. IEEE Transactions on Pattern Analysis and Machine Intelligence 19(7):711-720 1997.
3. A. J. Colmenarez and T. S. Huang. Face detection with infor mation-based maximum discrimination. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition pages 782-787 1997.
4. A. P. Dempster N. M. Laird and D. B. Rubin. Maximum likelihood from incomplete data via the em algorithm. Joruanl of the Royal Statistical Society 39(1):1-38 1977.
5. R. O. Duda and P. E. Hart. Pattern Classification and Scene Analysis. John Wiely New York 1973.
6. B. J. Frey A. Colmenarez and T. S. Huang. Mixtures of local subspaces for face recognition. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition pages 32-37 1998.
7. Z. Ghahramani and G. E. Hinton. The em algorithm for mixtures of factor analyzers. Technical Report CRG-TR-96-1 Department of Computer Science Universi ty of Toronto 1996. Available at ftp://ftp. cs.toronto.edu/pub/zoubin/tr-96-1. ps. gz.
8. D. B. Graham and N. M. Allinson. Characterizing virtual eigensignatures for general purpose face recognition. In H. Wechs ler P. J. Phillips V. Bruce F. Fogelman-Soulie and T. S. Huang editors Face Recognition: From Theory to Applications volume 163 of NATO ASI Series F Computer and Systems Sciences pages 446-456. Springer 1998.
9. P. Hallinan. A Deformable Model for Face Recognition Under Arbitrary Lighting Conditions. PhD thesis Harvard University 1995.
10. G. E. Hinton P. Dayan and M. Revow. Modeling the manifolds of ima ges of handwritten digits. IEEE Trans. Neural Networks 8(1):65-74 1997.
11. T. Kohonen. Self Organizing Map. Springer 1996.
12. B. Moghaddam and A. Pentland. Probabilistic visual learning for object recognition. IEEE Transactions on Pattern Analysis and Machine Intelligence 19(7):696-710 1997.
13. E. Osuna R. Freund and F. Girosi. Traini ng support vector machines: an application to face detection. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition pages 130-136 1997.
14. C. Papageorgiou M. O ren and T. Poggio. A general framework for object detection. In Proceedings of the Fifth International Conference on Computer Vision pages 555-562 1998.
15. P. J. Phillips H. Moon S. Rizvi and P. Rauss. The feret evaluation. In H. Wechsler P. J. Phillips V. Bruce F. Fogelman-Soulie and T. S. Huang editors Face Recognition: From Theory to Applications volume 163 of NATO ASI Series F Computer and Systems Sciences pages 244-261. Springer 1998.
16. R. J. Qian and T. S. Huang. Object detection using hierarchical mrf and map estimation. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition pages 186-192 1997.
17. A. N. Rajagopalan K. S. Kumar J. Karlekar R. Manivasakan and M. M. Patil. Finding faces in photographs. In Proceedings of the Sixth International Conference on Computer Vision pages 640-645 1998.
18. H. Rowley S. Baluja and T. Kanade. Neural network-based face detection. IEEE Transactions on Pattern Analysis and Machine Intelligence 20(1):23-38 1998.
19. H. Rowley S. Baluja and T. Kanade. Rotation invariant neural network-based face detection. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition pages 38-44 1998.
20. F. S. Samaria. Face Recognition Using Hidden Markov Models. PhD thesis University of Cambridge 1994.
21. H. Schneiderman and T. K anade. Probabilistic modeling of local appearance and spatial relationships for object recognition. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition pages 45-51 1998.
22. K.-K. Sung T. Poggio Example-based learning for view-based human face detection. IEEE Transactions on Pattern Analysis and Machine Intelligence 20 1 39-51 1998.
23. M.-H. Yang N. Ahuja and D. Kriegman. A survey on face detection methods. 2000. To be submitted.