Glasses detection by boosting simple wavelet features

We propose a novel method for glasses detection. The glasses detectors are learned by using a variation of boosting algorithm, called real Adaboost, to boost simple wavelet feature based Look-Up-Table type weak classifiers. Two types of wavelet features, Haar and Gabor, have been investigated. Experiments results are reported to show that our method has very high correctness and extremely fast running speed. Based on this method we have developed a glasses detection system which can detect the glasses in facial images automatically.

[1]  Harry Wechsler,et al.  The FERET database and evaluation procedure for face-recognition algorithms , 1998, Image Vis. Comput..

[2]  Shiguang Shan,et al.  Unified Framework For Classifying Facial Images Based On Facial Attribute- Specific Subspaces And Minimum Reconstruction Error , 2002 .

[3]  Bo Wu,et al.  Fast rotation invariant multi-view face detection based on real Adaboost , 2004, Sixth IEEE International Conference on Automatic Face and Gesture Recognition, 2004. Proceedings..

[4]  Yoram Singer,et al.  Improved Boosting Algorithms Using Confidence-rated Predictions , 1998, COLT' 98.

[5]  Robert Mariani,et al.  Glasses detection and extraction by deformable contour , 2000, Proceedings 15th International Conference on Pattern Recognition. ICPR-2000.

[6]  Horst Bunke,et al.  Towards Detection of Glasses in Facial Images , 1998, Proceedings. Fourteenth International Conference on Pattern Recognition (Cat. No.98EX170).

[7]  Paul A. Viola,et al.  Rapid object detection using a boosted cascade of simple features , 2001, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001.

[8]  Shuicheng Yan,et al.  Multi-view face alignment using direct appearance models , 2002, Proceedings of Fifth IEEE International Conference on Automatic Face Gesture Recognition.

[9]  Tong Wang,et al.  A two-stage approach to automatic face alignment , 2003, International Symposium on Multispectral Image Processing and Pattern Recognition.

[10]  Haiyuan Wu,et al.  Glasses frame detection with 3D Hough transform , 2002, Object recognition supported by user interaction for service robots.

[11]  John G. Daugman,et al.  Complete discrete 2-D Gabor transforms by neural networks for image analysis and compression , 1988, IEEE Trans. Acoust. Speech Signal Process..