Face detection based on kernel fisher discriminant analysis

Authors:
Yuanjian Feng;Pengfei Shi
Affiliations:
Institute of Image Processing and Pattern Recognition, Shanghai Jiaotong University, Shanghai, China;Institute of Image Processing and Pattern Recognition, Shanghai Jiaotong University, Shanghai, China
Venue:
FGR' 04 Proceedings of the Sixth IEEE international conference on Automatic face and gesture recognition
Year:
2004

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Abstract

This paper presents a face detection method based on Kernel Fisher Discriminant analysis (KFD). Kernel based methods have been extensively investigated both in theories and applications, such as SVM and Kernel PCA. Using the kernel trick, Linear Fisher Discriminant can be extended to non-linear case. Since the distribution of face patterns is very complex and highly nonlinear, using nonlinear classification tools can hopefully tackle the problem of face detection. We explore the application of KFD in the task of frontal face detection. The experimental results prove the effectiveness of KFD in the face detection problem.