Anti-faces for detection

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 1842, Issue , 2000, Pages 134-148

  Keren, Daniel ^a   Osadchy, Margarita ^a   Gotsman, Craig ^b  

^a UNIVERSITY OF HAIFA   (Israel)

^b TECHNION ISRAEL INSTITUTE OF TECHNOLOGY   (Israel)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER VISION; ERRORS; FACE RECOGNITION; LINEAR TRANSFORMATIONS; MATHEMATICAL TRANSFORMATIONS; PROBABILITY DISTRIBUTIONS; SUPPORT VECTOR MACHINES;

ALGORITHM'S PERFORMANCE; DETECTION METHODS; DETECTION PROBLEMS; FAST DETECTION ALGORITHM; IMAGE COLLECTIONS; IMPLICIT REPRESENTATION; PROBABILISTIC ASSUMPTIONS; SUPPORT VECTOR;

OBJECT DETECTION;

EID: 84944222760     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/3-540-45054-8_9     Document Type: Conference Paper

References (25)

1. P. N. Belhumeur, P. Hespanha, and D. J. Kriegman. Eigenfaces vs. fisherfaces: Recognition using class specific linear projection. IEEE Trans. on Pattern Analysis and Machine Intelligence, 19(7):711-720, 1997.
2. J. Ben-Arie and K.R. Rao. A novel approach for template matching by nonorthogonal image expansion. IEEE Transactions on Circuits and Systems for Video Technology, 3(1):71-84, 1993.
3. S. Geman and D. Geman. Stochastic relaxation, Gibbs distribution, and the Bayesian restoration of images. IEEE Trans. on Pattern Analysis and Machine Intelligence, 6:721-741, June 1984.
4. D. Keren and M. Werman. Probabilistic analysis of regularization. IEEE Trans. on Pattern Analysis and Machine Intelligence, 15:982-995, October 1993.
5. Y. Lamdan and H. J. Wolfson. Geometric hashing: A general and efficient modelbased recognition scheme. In Proc. Int'l. Conf. Comp. Vision, pages 238-249, 1988.
6. C.H Lo and H.S. Don. 3-D moment forms: Their construction and application to object identi_cation and positioning. IEEE Trans. on Pattern Analysis and Machine Intelligence, 11:1053-1064, 1989.
7. B. Moghaddam and A. Pentland. Probabilistic visual learning for object representation. IEEE Trans. on Pattern Analysis and Machine Intelligence, 19(7):696-710, 1997.
8. H. Murase and S. K. Nayar. Visual learning and recognition of 3d objects from appearance. International Journal of Computer Vision, 14(1):5-24, 1995.
9. E. Osuna, R. Freund, and F. Girosi. Training support vector machines: An application to face detection. In IEEE Conference on Computer Vision and Pattern Recognition, 1997.
10. C. P. Papageorgiou, M. Oren, and T. Poggio. A general framework for object detection. In International Conference on Computer Vision, pages 555-562, 1998.
11. M. Pontil and A. Verri. Support vector machines for 3d object recognition. IEEE Trans. on Pattern Analysis and Machine Intelligence, 20(6):637-646, 1998.
12. K.R. Rao and J. Ben-Arie. Nonorthogonal image expansion related to optimal template matching in complex images. CVGIP: Graphical Models and Image Processing, 56(2):149-160, 1994.
13. D. Roobaert and M.M. Van Hulle. View-based 3d object recognition with support vector machines. In IEEE International Workshop on Neural Networks for Signal Processing, pages 77-84, USA, 1999.
14. H. A. Rowley, S. Baluja, and T. Kanade. Neural network-based face detection. IEEE Trans. on Pattern Analysis and Machine Intelligence, 20(1):23-38, 1998.
15. H. A. Rowley, S. Baluja, and T. Kanade. Rotation invariant neural network-based face detection. In IEEE Conference on Computer Vision and Pattern Recognition, 1998.
16. G. Stockham, T.M. Cannon, and R.B. Ingebresten. Blind deconvolution through digital signal processing. Proceedings of the IEEE, 63:678-692, 1975.
17. K.K. Sung and T. Poggio. Example-based learning for view-based human face detection. IEEE Trans. on Pattern Analysis and Machine Intelligence, 20(1):39-51, 1998.
18. D. L. Swets and J. Weng. Using discriminant eigenfeatures for image retrieval. IEEE Trans. on Pattern Analysis and Machine Intelligence, 18(8):831-836, 1996.
19. D. Terzopoulos. Regularization of visual problems involving discontinuities. IEEE Trans. on Pattern Analysis and Machine Intelligence, 8:413-424, August 1986.
20. M. Turk and A. Pentland. Eigenfaces for recognition. Journal of Cognitive Neuroscience, 3(1):71-86, 1991.
21. M. Turk and A. Pentland. Face recognition using eigenfaces. In Proceedings of the Int'l Conf. on Computer Vision and Pattern Recognition, pages 586-591, 1991.
22. Matthew Turk. Personal communication, December 1999.
23. M. Uenohara and T. Kanade. Use of the fourier and karhunen-loeve decomposition for fast pattern matching with a large set of templates. IEEE Trans. on Pattern Analysis and Machine Intelligence, 19(8):891-897, 1997.
24. V. N. Vapnik. The Nature of Statistical Learning Theory. Berlin: Springer-Verlag, 1995.
25. I. Weiss. Geometric invariants and object recognition. International Journal of Computer Vision, 10:3:201-231, June 1993.