Abstract
Gabor-based Face representation has achieved great success in face recognition, while whether and how it can be applied to face detection is rarely studied. This paper originally investigates the Gabor feature based face detection method, and proposes a coarse-to-fine hierarchical face detector combining the high efficiency of Harr features and the excellent discriminating power of the Gabor features. Gabor features are AdaBoosted to form the final verifier after the cascade of Harr-based AdaBoost face detector. Extensive experiments are conducted on several face databases and verified the effectiveness of the proposed approach.
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References
Buhlmann, P., Yu, B.: Invited discussion on Additive logistic regressions: a statistical view of boosting (Friedman, Hastie and Tibshirani). The Annual of Statistics 28(2), 377–386 (2000)
Chen, J., Gao, W.: Expand Training Set for Face Detection by GA Re-sampling. In: The 6th IEEE International Conference on Automatic Face and Gesture Recognition (FG2004), pp. 73–79 (2004)
Fasel, I.R., Bartlett, M.S., Movellan, J.R.: A comparison of Gabor filter methods for automatic detection of facial landmarks. In: Proceedings of the 5th International Conference on Face and Gesture Recognition (2002)
Huang, L.-L., Shimizu, A., Kobatake, H.: Classification-Based Face Detection Using Gabor Filter Features. In: The 6th IEEE International Conference on Automatic Face and Gesture Recognition (FG2004), pp. 397–402 (2004)
Hsu, R.L., Abdel-Mottaleb, M., Jain, A.K.: Face detection in color images. IEEE Trans. Pattern Anal. Machine Intell. 24, 696–706 (2002)
Liu, C., Shum, H.Y.: Kullback-Leibler Boosting. In: Proceedings of the 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2003 (2003)
Li, S.Z., Zhu, L., Zhang, Z.Q., Blake, A., Zhang, H.J., Shum, H.: Statistical Learning of Multi-View Face Detection. In: Proceedings of the 7th European Conference on Computer Vision (2002)
Liu, C.J.: A Bayesian Discriminating Features Method for Face Detection. IEEE Trans. Pattern Analysis and Machine Intelligence 25, 725–740 (2003)
Osuna, E., Freund, R., Girosi, F.: Training support vector machines: An application to face detection. In: Proc. IEEE Computer Soc. Conf. on Computer Vision and Pattern Recognition, June 1997, pp. 130–136 (1997)
Papageorgiou, C.P., Oren, M., Poggio, T.: A general framework for object detection. In: Proc. 6th Int. Conf. Computer Vision, January 1998, pp. 555–562 (1998)
Phillips, P.J., Moon, H., Rauss, P.: The FERET Evaluation Methodology for Face-Recognition Algorithms. Proceedings of Computer Vision and Pattern Recognition, Puerto Rico, 137–143 (1997)
Rowley, H.A., Baluja, S., Kanade, T.: Neural Network-Based Face Detection. IEEE Tr. Pattern Analysis and Machine Intel. 20, 23–38 (1998)
Rowley, H.A., Baluja, S., Kanade, T.: Rotation Invariant Neural Network-Based Face Detection. In: Conf. Computer Vision and Pattern Rec., pp. 38–44 (1998)
Schneiderman, H., Kanade, T.: A Statistical Method for 3D Object Detection Applied to Faces. Computer Vision and Pattern Recognition, 746–751 (2000)
Sung, K.K., Poggio, T.: Example-Based Learning for View-Based Human Face Detection. IEEE Trans. on PAMI 20(1), 39–51 (1998)
Viola, P., Jones, M.: Rapid Object Detection Using a Boosted Cascade of Simple Features. In: Conf. Computer Vision and Pattern Recognition, pp. 511–518 (2001)
Wiskott, L., Fellous, J., Kruger, N., von der Malsburg, C.: Face recognition by elastic bunch graph matching. IEEE Trans. PAMI 19(7), 669–775 (1997)
Xiao, R., Li, M.J., Zhang, H.J.: Robust Multipose Face Detection in Images. IEEE Trans on Circuits and Systems for Video Technology 14(1), 31–41 (2004)
Yang, M.H., Roth, D., Ahuja, N.: A SNoW-Based Face Detector. In: Advances in Neural Information Processing Systems, vol. 12, pp. 855–861. MIT Press, Cambridge (2000)
Yang, M.H., Kriegman, D., Ahuja, N.: Detecting Faces in Images: A Survey. IEEE Tr. Pattern Analysis and Machine Intelligence 24, 34–58 (2002)
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Chen, J., Shan, S., Yang, P., Yan, S., Chen, X., Gao, W. (2004). Novel Face Detection Method Based on Gabor Features. In: Li, S.Z., Lai, J., Tan, T., Feng, G., Wang, Y. (eds) Advances in Biometric Person Authentication. SINOBIOMETRICS 2004. Lecture Notes in Computer Science, vol 3338. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30548-4_11
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DOI: https://doi.org/10.1007/978-3-540-30548-4_11
Publisher Name: Springer, Berlin, Heidelberg
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