This Article 
   
 Share 
   
 Bibliographic References 
   
 Add to: 
 
Digg
Furl
Spurl
Blink
Simpy
Google
Del.icio.us
Y!MyWeb
 
 Search 
   
Example-Based Learning for View-Based Human Face Detection
January 1998 (vol. 20 no. 1)
pp. 39-51

Abstract—We present an example-based learning approach for locating vertical frontal views of human faces in complex scenes. The technique models the distribution of human face patterns by means of a few view-based "face" and "nonface" model clusters. At each image location, a difference feature vector is computed between the local image pattern and the distribution-based model. A trained classifier determines, based on the difference feature vector measurements, whether or not a human face exists at the current image location. We show empirically that the distance metric we adopt for computing difference feature vectors, and the "nonface" clusters we include in our distribution-based model, are both critical for the success of our system.

[1] D. Beymer, A. Shashua, and T. Poggio, "Example Based Image Analysis and Synthesis," AIM-1431, Artificial Intelligence Laboratory, Massachusetts Institute of Tech nology, 1993.
[2] M. Bichsel, "Strategies of Robust Objects Recognition for Automatic Identification of Human Faces," PhD thesis, ETH, Zurich, 1991.
[3] R. Brunelli and T. Poggio, "Face Recognition: Features vs. Templates," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 15, no. 10, pp. 1,042-1,053, Oct. 1993.
[4] M.C. Burl, U. Fayyad, P. Perona, P. Smyth, and M.P. Burl, "A Trainable Tool for Finding Small Volcanoes in SAR Imagery of Venus," CNS TR-34, Calif. Inst. of Tech nology, 1993.
[5] R.O. Duda and P.E. Hart, Pattern Classification and Scene Analysis.New York: John Wiley and Sons Inc., 1973.
[6] W.E.L. Grimson and T. Lozano-Perez, "Model-Based Recognition and Localization From Sparse Range Data," A. Rosenfeld, ed., Techniques for 3-D Machine Perception.Amsterdam: North-Holland, 1985.
[7] G. Hinton, M. Revow, and P. Dayan, "Recognizing Handwritten Digits Using Mixture of Linear Models," Proc. Advances in Neural Information Processings Systems, vol. 7, 1995.
[8] M. Kirby and L. Sirovich,“Application of Karhunen-Loève procedure for the characterization of human faces,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 12, no. 1, pp. 103-108, Jan. 1990.
[9] B. Kumar, D. Casasent, and H. Murakami, "Principal Component Imagery for Statistical Pattern Recognition Correlators," Optical Eng., vol. 21, no. 1, Jan./Feb. 1982.
[10] A. Mahalanobis, A. Forman, N. Day, M. Bower, and R. Cherry, "Multi-Class SAR ATR Using Shift-Invariant Correlation Filters," Pattern Recognition, vol. 27, no. 4, pp. 619-626, 1994.
[11] M. Oren, C. Papageorgiou, P. Sinha, E. Osuna, and T. Poggio, Pedestrian Detection Using Wavelet Templates Proc. Computer Vision and Pattern Recognition, pp. 193-199, June 1997.
[12] A. Pentland, B. Moghaddam, and Starner, "View-Based and Modular Eigenspaces for Face Recognition," Proc. IEEE Conf. Computer Vision and Pattern Recognition, 1994, pp. 84-91.
[13] T. Poggio and T. Vetter, "Recognition and Structure From One (2D) Model View: Observations on Prototypes, Object Classes, and Symmetries," AIM-1347, Artificial Intelligence Laboratory, Massachusetts Institute of Tech nology, 1992.
[14] D. Rumelhart and J. McClelland, Parallel Distributed Processing, vol. 1. Cambridge, Mass.: MIT Press, 1986.
[15] P. Sinha, "Object Recognition via Image Invariants: A Case Study," Investigative Ophthalmology and Visual Science, vol. 35, pp. 1,735-1,740, May 1994.
[16] K. Sung and T. Poggio, "Example-Based Learning for View-Based Human Face Detection," Proc. Image Understanding Workshop, vol. 2, pp. 843-850, 1994.
[17] K. Sung, "Learning and Example Selection for Object and Pattern Detection," PhD thesis, Massachusetts Institute of Tech nology, 1995.
[18] M. Turk and A. Pentland, "Eigenfaces for Recognition," J. Cognitive Neuroscience, vol. 3, no. 1, pp. 71-86, 1991.
[19] A. Yuille, P. Hallinan, and D. Cohen, "Feature Extraction From Faces Using Deformable Templates," Int'l J. Computer Vision, vol. 8, no. 2, pp. 99-111, 1992.

Index Terms:
Face detection, object detection, example-based learning, example selection, pattern recognition, view-based recognition, density estimation, Gaussian mixture model.
Citation:
Kah-Kay Sung, Tomaso Poggio, "Example-Based Learning for View-Based Human Face Detection," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 20, no. 1, pp. 39-51, Jan. 1998, doi:10.1109/34.655648
Usage of this product signifies your acceptance of the Terms of Use.