Local Feature Based 3D Face Recognition

This paper presents a 3D face recognition system based on geometrically localized facial features. We propose the feature extraction procedure using the geometrical characteristics of a face. We extract three curvatures, eight invariant facial feature points and their relative features. These features are directly applied to face recognition algorithms which are a depth-based DP (Dynamic Programming) and a feature-based SVM (Support Vector Machine). Experimental results show that face recognition rates based on the depth-based DP and the feature-based SVM are 95% for 20 people and 96% for 100 people, respectively.

• Type: Conference
• Year: 2005
• Where: AVBPA
• Authors: Yonguk Lee, Hwanjong Song, Ukil Yang, Hyungchul Shin, Kwanghoon Sohn
• Keywords: AVBPA 2005, Face Recognition, Facial Feature, Feature-based Svm, Multimedia