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Convolutional Face Finder: A Neural Architecture for Fast and Robust Face Detection
November 2004 (vol. 26 no. 11)
pp. 1408-1423
In this paper, we present a novel face detection approach based on a convolutional neural architecture, designed to robustly detect highly variable face patterns, rotated up to \pm20 degrees in image plane and turned up to \pm60 degrees, in complex real world images. The proposed system automatically synthesizes simple problem-specific feature extractors from a training set of face and nonface patterns, without making any assumptions or using any hand-made design concerning the features to extract or the areas of the face pattern to analyze. The face detection procedure acts like a pipeline of simple convolution and subsampling modules that treat the raw input image as a whole. We therefore show that an efficient face detection system does not require any costly local preprocessing before classification of image areas. The proposed scheme provides very high detection rate with a particularly low level of false positives, demonstrated on difficult test sets, without requiring the use of multiple networks for handling difficult cases. We present extensive experimental results illustrating the efficiency of the proposed approach on difficult test sets and including an in-depth sensitivity analysis with respect to the degrees of variability of the face patterns.

[1] M.-H. Yang, D.J. Kriegman, and N. Ahuja, "Detecting Faces in Images: A Survey," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 24, no. 1, Jan. 2002, pp. 34-58.
[2] E. Hjelmås and B.K. Low, Face Detection: A Survey Computer Vision and Image Understanding, vol. 83, pp. 236-274, 2001.
[3] V. Govindaraju, Locating Human Faces in Photographs Int'l J. Computer Vision, vol. 19, no. 2, pp. 129-146, 1996.
[4] G. Yang and T.S. Huang, Human Face Detection in Complex Background Pattern Recognition, vol. 27, no. 1, pp. 53-63, 1994.
[5] C. Garcia and G. Tziritas, “Face Detection Using Quantized Skin Color Regions Merging and Wavelet Packet Analysis,” IEEE Trans. Multimedia, vol. 1, no. 3, pp. 264-277, Sept. 1999.
[6] R. Féraud, O.J. Bernier, J.-E. Viallet, and M. Collobert, “A Fast and Accurate Face Detection Based on Neural Network,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 23, no. 1, pp. 42-53, Jan. 2001.
[7] B. Low and M. Ibrahim, A Fast and Accurate Algorithm for Facial Feature Segmentation Proc. Int'l Conf. Image Processing, 1997.
[8] C.C. Lin and W.C. Lin, Extracting Facial Features by an Inhibitory Mechanism Based on Gradient Distributions Pattern Recognition, vol. 29, pp. 2079-2101, 1996.
[9] B. Moghaddam and A. Pentland, “Probabilistic Visual Learning for Object Representation,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 19, no. 7, pp. 696-710, July 1997.
[10] L. Wiskott, J.M. Fellous, N. Kruger, and C. von der Malsburg, Face Recognition by Elastic Bunch Graph Matching IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 19, no. 7, pp. 775-779, July 1997.
[11] C. Garcia, G. Simandiris, and G. Tziritas, A Feature-Based Face Detector Using Wavelet Frames Proc. Int'l Workshop Very Low Bit Coding, pp. 71-76, 2001.
[12] K. Yow and R. Cipolla, Feature-Based Human Face Detection Image and Vision Computing, vol. 15, no. 9, pp. 713-735, 1997.
[13] S. Jeng, H. Yao, C. Han, M. Chern, and Y. Liu, Facial Feature Detection Using Geometrical Face Model: An Efficient Approach Pattern Recognition, vol. 31, no. 3, pp. 273-282, 1998.
[14] D. Maio and D. Maltoni, Real-Time Face Location on Gray-Scale Static Images Pattern Recognition, vol. 33, pp. 1525-1539, 2000.
[15] Y. Lecun, L. Bottou, Y. Bengio, and P. Haffner, “Gradient-Based Learning Applied to Document Recognition,” Proc. IEEE, vol. 86, no. 11, pp. 2278–2324, 1998.
[16] K.K. Sung and T. Poggio, "Example-Based Learning for View-Based Human Face Detection," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 20, no. 1, pp. 39-50, Jan. 1998.
[17] M. Yang, D. Kriegman, and N. Ahuja, Face Detection Using Multimodal Density Models Computer Vision and Image Understanding, vol. 84, pp. 264-284, 2001.
[18] A.J. Colmenarez and T.S. Huang, Face Detection with Information-Based Maximum Discrimination Proc. IEEE Conf. Computer Vision and Pattern Recognition, pp. 782-787, 1997.
[19] C. Garcia and G. Tziritas, Wavelet Packet Analysis for Face Recognition Image and Vision Computing, vol. 18, no. 4, pp. 289-297, 2000.
[20] H. Schneiderman and T. Kanade, "A Statistical Method for 3D Object Detection Applied to Faces and Cars," Proc. IEEE Computer Vision and Pattern Recognition (CVPR 00), IEEE CS Press, 2000, pp. 746—751.
[21] C. Liu, A Bayesian Discriminating Features Method for Face Detection IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 25, no. 6, pp. 725-740, June 2003.
[22] E. Osuna, R. Freund, and F. Girosi, Training Support Vector Machines: An Application to Face Detection Proc. IEEE Conf. Computer Vision and Pattern Recognition, pp. 17-19, 1997.
[23] H. Rowley, S. Baluja, and T. Kanade, "Neural Network-Based Face Detection," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 20, no. 1, Jan. 1998, pp. 23-38.
[24] D. Roth, M.-H. Yang, and N. Ahuja, A SNoW-Based Face Detector Advances in Neural Information Processing Systems 12, pp. 855-861, MIT Press, 2000.
[25] F. Fleuret and D. Geman, Coarse-to-Fine Face Detection Int'l J. Computer Vision, vol. 20, pp. 1157-1163, 2003.
[26] P. Viola and M. Jones, Rapid Object Detection Using a Boosted Cascade of Simple Features Proc. IEEE Conf. Computer Vision and Pattern Recognition, 2001.
[27] S. Li, L. Zhu, Z. Zhang, and A. Blake, H. Zhang, and H. Shum, Statistical Learning of Multi-View Face Detection Proc. Seventh European Conf. Computer Vision, pp. 67-81, 2002.
[28] Y. LeCun, Generalization and Network Design Strategies Connectionism in Perspective, R. Pfeifer, Z. Schreter, F. Fogelman, and L. Steels, eds., Zurich, Switzerland: Elsevier, 1989.
[29] Y. LeCun, B. Boser, J. Denker, D. Henderson, R. Howard, W. Hubbard, and L. Jackel, Handwritten Digit Recognition with a Back-Propagation Network Advances in Neural Information Processing Systems 2, D. Touretzky, ed. Denver: Morgan Kaufman, pp. 396-404, 1990.
[30] G. Martin, Centered-Object Integrated Segmentation and Recognition of Overlapping Hand-Printed Characters Neural Computation, vol. 5, pp. 419-429, 1993.
[31] J. Wang and J. Jean, Multi-Resolution Neural Networks for Omnifont Character Recognition Proc. Int'l Conf. Neural Networks, vol. 3, pp. 1588-1593, 1993.
[32] S. Lawrence, C.L. Giles, A.C. Tsoi, and A.D. Back, “Face Recognition: A Convolutional Neural-Network Approach,” IEEE Trans. Neural Networks, vol. 8, pp. 98-113, 1997.
[33] R. Vaillant, C. Monrocq, and Y. Le Cun, Original Approach for the Localisation of Objects in Images IEEE Proc. Visual Image Signal Process., vol. 141, no. 4, Aug. 1994.
[34] D. Hubel and T. Wiesel, Receptive Fields, Binocular Interaction and Functional Architecture in the Cat's Visual Cortex J. Physiology, vol. 160, pp. 106-154, 1962.
[35] K. Fukushima, Cognitron: A Self-Organizing Multilayered Neural Network Biological Cybernetics, vol. 20, pp. 121-136, 1975.
[36] M. Mozer, The Perception of Multiple Objects: A Connectionist Approach Connectionism in Perspective. Cambridge, Mass.: MIT Press-Bradford Books, 1991.
[37] C. Garcia and M. Delakis, A Neural Architecture for Fast and Robust Face Detection Proc. Int'l Conf. Pattern Recognition, vol. 2, pp. 44-48, 2002.
[38] H.A. Rowley, S. Baluja, and T. Kanade, “Rotation Invariant Neural Network-Based Face Detection,” Proc. IEEE Conf. Computer Vision and Pattern Recognition, 1998.
[39] P. Viola and M. Jones, Robust Real-Time Object Detection Proc. ICCV Second Int'l Workshop Statistical and Computational Theories of Vision Modelling, Learning, Computing, and Sampling, July 2001.

Index Terms:
Face detection, neural networks, machine learning, convolutional networks.
Citation:
Christophe Garcia, Manolis Delakis, "Convolutional Face Finder: A Neural Architecture for Fast and Robust Face Detection," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 26, no. 11, pp. 1408-1423, Nov. 2004, doi:10.1109/TPAMI.2004.97
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