Face detection has been an important research topic over the last 20 years. It is commonly used as a first step in face recognition and several techniques were applied in face detection, going from geometrical methods such as model matching to connectionist methods such as neural networks. This work presents a face detection system that uses a Bayesian network to combine information from different computational cheap visual operators, and is part of an ongoing project that uses a webcam to perform a reliable and accurate eye tracking. The face detection is the first step in this project. The aim in this work is to show that combining simple features in a Bayesian network helps improving the performance in a face detector system, increasing the detection rate and speeding up the face detection process.
References
Ballard, D. H. (1991). Animate vision., Artificial Intelligence 48 57–86.
Chai, D. and Ngan, K. N. (1998). Locating facial region of a head-and-shoulders color image. In, Third IEEE International Conference on Automatic Face and Gesture Recognition (ICAFGR) 124–129. Nara, Japan.
Chen, Q., Wu, H. and Yachida, M. (1995). Face detection by fuzzy pattern matching. In, Proceedings of The International Conference on Computer Vision 591–596.
Cheng, J., Bell, D. and Liu, W. (1998). Learning Bayesian networks from data: An efficient approach based on information theory. Technical Report Department of Computer Science Univ., Alberta.
Cootes, T. F. and Taylor, C. J. (1996). Locating faces using statistical feature detectors. In, Second IEEE International Conference on Automatic Face and Gesture Recognition (ICAFGR) 204. Killington, USA.
Huang, K. S. and Trivedi, M. M. (2008). Integrated detection, tracking, and recognition of faces with omnivideo array in intelligent environments., Journal on Image and Video Processing 8 1–19.
Jensen, F. V. (1996)., An Introduction to Bayesian Networks. Springer.
Kadoury, S. and Levine, M. D. (2007). Face detection in gray scale images using locally linear embeddings., Computer Vision and Image Understanding 105 1–20.
Mamalet, F., Roux, S. and Garcia, C. (2007). Real-time video convolutional face finder on embedded platforms., EURASIP Journal on Embedded Systems 2007, Article ID 21724.
Marengoni, M., Hanson, A., Zilberstein, S. and Riseman, E. (2003). Decision making and uncertainty management in a 3D reconstruction system., IEEE Transactions on Pattern Analysis and Machine Intelligence 25 852–858.
Masip, D., Bressan, M. and Vitri J. (2005). Feature extraction methods for real-time face detection and classification., EURASIP Journal on Applied Signal Processing 2005 2061–2071.
Osuna, E., Freud, R. and Girosi, F. (1997). Training support vector machines: An application to face detection. In, Proceedings of The IEEE Conference on Computer Vision and Pattern Recognition 130–136.
Pearl, J. (1988)., Probabilistic Reasoning in Intelligent System: Networks of Plausible Inference. Morgan Kaufmann.
Mathematical Reviews (MathSciNet):
MR965765
Pearl, J. (2001). Bayesian network., Handbook of Brain theory and Neural Networks. MIT Press.
Pham, T. V., Worring, M. and Smeulders, A. W. M. (2002). Face detection by aggregated Bayesian network classifiers., Pattern Recognition Letters 23 451–461.
Rowley, H., Bajula, S. and Kanade, T. (1996). Neural network-based face detection. In, Proceedings of The IEEE Conference on Computer Vision and Pattern Recognition 203–208.
Rowley, H., Bajula, S. and Kanade, T. (1998). Rotation invariant neural network-based face detection. In, Proceedings of The IEEE Conference on Computer Vision and Pattern Recognition 38–44.
Scheneiderman, H. and Kanade, T. (2000). A statistical method for 3D object detection applied to faces and cars. In, Proceedings of The International Conference on Computer Vision.
Schneiderman, H. and Kanade, T. (1998). Probabilistic modeling of local appearance and spatial relationship for object recognition. In, Proceedings of The IEEE Conference on Computer Vision and Pattern Recognition 45–51.
Sebe, N., Cohen, I., Cozman, F. G., Gevers, T. and Huang, T. S. (2005). Learning probabilistic classifiers for humancomputer interaction applications., Multimedia Systems 10 484–498.
Sung, K. and Poggio, T. (1998). Example-based learning for view-based human face detection., IEEE Transactions on Pattern Analysis and Machine Intelligence 20 39–51.
Vezhnevets, V., Sazonov, V. and Andreeva A. (2003). A survey on pixel-based skin color detection techniques. In, Proceedings of the 13th Graphicon 85–92.
Viola, P. and Jones, M. J. (2004). Robust real-time face detection., International Journal of Computer Vision 57 137–154.
Wu, H., Chen, Q. and Yachida, M. (1994). Face detection from color images using a fuzzy pattern matching method., IEEE Transactions on Pattern Analysis and Machine Intelligence 21 53–63.
Wu, H., Yokoyama, T., Pramadihanto, D. and Yachida, M. (1996). Face and facial feature extraction from color image. In, Second IEEE International Conference on Automatic Face and Gesture Recognition (ICAFGR) 345–350. Killington, USA.
Yang, M. H., Ahuja, N. and Kreigman, D. (2000). A SNoW-based face detector. In, Advances in Neural Information Processing Systems (S. A. Solla, T. K. Leen and K. R. Muller, eds.) 12 855–861. MIT Press.
Yang, M. H., Ahuja, N. and Kreigman, D. (2000). Mixtures of linear subspaces for face detection. In, Fourth IEEE International Conference on Automatic Face and Gesture Recognition (ICAFGR) 70–76.
Yang, M. H., Kriegman, D. J. and Ahuja, N. (2002). Detecting faces in images: A survey., IEEE Transactions on Pattern Analysis and Machine Intelligence 24 34–58.
Yow, K. C. and Cipolla, R. (1997). Feature-based human face detection., Image and Vision Computing 15 713–735.