Abstract
This paper presents a novel face detection approach in color images. We employ spatial histograms as robust features for face detection. The spatial histograms consist of marginal distribution of color image information. Facial texture and shape are preserved by the spatial histogram representation. A hierarchical classifier combining histogram matching and support vector machine is utilized to identify face and non-face. The experiments show that this approach performs an excellent capability for face detection, and it is robust to lighting changes.
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Yang, M.H., Kriegman, D.J., Ahuja, N.: Detecting Faces in Images: A Survey. IEEE Translations on Pattern Analysis And Machine Intelligence 24(1), 34–58 (2002)
Rowley, H.A., Baluja, S., Kanade, T.: Neural Network-Based Face Detection. IEEE Translations on Pattern Analysis And Machine Intelligence 20(1), 29–38 (1998)
Sung, K.K., Poggio, T.: Example-Based Learning for View-Based Human Face Detection. IEEE Translations on Pattern Analysis And Machine Intelligence 20(1), 39–50 (1998)
Osuna, E., Freund, R., Girosi, F.: Training Support Vector Machines: an Application to Face Detection. In: Proceedings of CVPR, pp. 130–136 (1997)
Menser, B., Muller, F.: Face detection in color images using principal component analysis. In: Proceedings of 7th International Congress on Image Processing and its Applications, pp. 13–15 (1999)
Schneiderman, H., Kanade, T.: A Statistical Method for 3D Object Detection Applied to Faces and Cars. In: IEEE Conference on Computer Vision and Pattern Recognition (2000)
Viola, P., Jones, M.: Robust Real Time Object Detection. In: IEEE ICCV Workshop on Statistical and Computational Theories of Vison (2001)
Li, S.Z., et al.: Statistical Learning of Multi-View Face Detection. In: Proc. of the 7th European Conf. on Computer Vision (2002)
Yow, K.C., Cipolla, R.: Feature-Based Human Face Detection. CUED/FINFENG/TR 249 (August 1996)
Miao, J., Yin, B.C., Wang, K.Q., Shen, L.S., Chen, X.C.: A hierarchical multiscale and multiangle system for human face detection in a complex background using gravity-center template. Pattern Recognition 32(7), 1237–1248 (1999)
Sobottka, K., Pitas, I.: A novel method for automatic face segmentation, facial feature extraction and tracking. Signal Processing: Image Communication 12(3), 263–281 (1998)
Sun, Q.B., Huang, W.M., Wu, J.K.: Face detection based on color and local symmetry information. In: Proceedings of Third IEEE International Conference on Automatic Face and Gesture Recognition, pp. 130–135 (1998)
Bernhard, F., Christian, K.: Real-Time Face Detection using Edge-Orientation Matching. In: Bigun, J., Smeraldi, F. (eds.) AVBPA 2001. LNCS, vol. 2091, pp. 78–83. Springer, Heidelberg (2001)
Garcia, C., Tziritas, G.: Face Detection Using Quantized Skin Color Regions Merging andWavelet Packet Analysis. IEEE Transactions on Multimedia 1(3), 264–277 (1999)
Pietikäinen, M., Ojala, T., Xu, Z.: Rotation-invariant texture classification using feature distributions. Pattern Recognition 33(1), 43–52 (2000)
Swain, M., Ballard, D.: Color indexing. Int. J. Computer Vision 7(1), 11–32 (1991)
Ojala, T., Pietikäinen, M., Mäenpää, T.: Multiresolution gray-scale and rotation invariant texture classification with local binary patterns. IEEE Transactions on Pattern Analysis and Macine Intelligence 24(7), 971–987 (2002)
Vapnik, V.: Statistical Learning Theory. Wiley, New York (1998)
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Zhang, H., Zhao, D. (2004). Spatial Histogram Features for Face Detection in Color Images. In: Aizawa, K., Nakamura, Y., Satoh, S. (eds) Advances in Multimedia Information Processing - PCM 2004. PCM 2004. Lecture Notes in Computer Science, vol 3331. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30541-5_47
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DOI: https://doi.org/10.1007/978-3-540-30541-5_47
Publisher Name: Springer, Berlin, Heidelberg
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