Fang Tianhong, Chen Qinghu, Liao Haibin, Qiu Yiming. Face Feature Weighted by Fusing Texture and Shape[J]. Geomatics and Information Science of Wuhan University, 2015, 40(3): 321-326+340.
Citation: Fang Tianhong, Chen Qinghu, Liao Haibin, Qiu Yiming. Face Feature Weighted by Fusing Texture and Shape[J]. Geomatics and Information Science of Wuhan University, 2015, 40(3): 321-326+340.

Face Feature Weighted by Fusing Texture and Shape

  • Textural and structural characteristics are two of the principal features of human faces,both of which have advantages and disadvantages for face recognition. In this paper,we propose a Gaussian weights based new feature combined with texture feature and structure feature approach. In this method,we first use a standard fiducial point detector to locating five face key-points(e. g.,the mid-point of the eye),and then a new feature will be generated dynamically by weighting the gray value of the pixel according to the distance between the pixel and its relative key-point. The new feature,originated from the texture feature,ties the geometric structural feature of the pixels and the key-point information and delivers better performance than the original texture feature for pose variations.Meanwhile,the five key-points are beneficial to part-based face recognition. Experimental results show that the new feature can improve recognition rates by about 5%than the original texture feature,and improved the part-based method by combining the new feature and the face blocking;achieving recogni-tion rates close to 100%for two different available databases.
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