Edge Eigenface Weighted Hausdorff Distance for Face Recognition

Huachun Tan Department of Transportation Engineering, Beijing Institute of Technology, Beijing, 100081, China E-mail: {tanhc }@bit.edu.cn

Yu-Jin Zhang Department of Electronic Engineering, Tsinghua University, Beijing, 100084, China E-mail: [email protected]

Wuhong Wang Department of Transportation Engineering, Beijing Institute of Technology, Beijing, 100081, China E-mail: { wangwuhong, 20903201, xionghui }@bit.edu.cn

Guangdong Feng Department of Transportation Engineering, Beijing Institute of Technology, Beijing, 100081, China E-mail: { wangwuhong, 20903201, xionghui }@bit.edu.cn

Hui Xiong Department of Transportation Engineering, Beijing Institute of Technology, Beijing, 100081, China E-mail: { wangwuhong, 20903201, xionghui }@bit.edu.cn

Jie Zhang Research Institute of Highway, Ministry of Transport of China, Beijing, 100088, China E-mail: [email protected]

Yong Li Department of Electrical Engineering, Notre Dame University E-mail: [email protected]

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Abstract

The different face regions have different degrees of importance for face recognition. In previous Hausdorff distance (HD) measures, points are treated as same importance, or weight different points that calculated from gray domain. In this paper, a new weighting function of HD based on the eigenface from edge domain, which reflects the discriminative properties of face edge images effectively, is proposed for face recognition. Experiments show the proposed method outperforms previous HD measures.

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Edge Eigenface Weighted Hausdorff Distance for Face Recognition

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Edge Eigenface Weighted Hausdorff Distance for Face Recognition

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