3D face recognition by constructing deformation invariant image

Authors:
Li Li;Chenghua Xu;Wei Tang;Cheng Zhong
Affiliations:
College of Information and Electrical Engineering, China Agricultural University, P.O. Box 62, Beijing 100083, PR China;Nufront Software Corporation, Beijing 100084, PR China;College of Information and Electrical Engineering, China Agricultural University, P.O. Box 62, Beijing 100083, PR China;National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100080, PR China
Venue:
Pattern Recognition Letters
Year:
2008

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Abstract

Based on the observation that facial surfaces across different expressions can be modeled as similar isometric transformations, in this paper a novel deformation invariant image for robust 3D face recognition is proposed. First, we obtain the depth image and the intensity image from the original 3D facial data. Then, geodesic level curves are generated by constructing radial geodesic distance image from the depth image. Finally, deformation invariant image is constructed by evenly sampling points from the selected geodesic level curves in the intensity image. Our experiments are based on the 3D CASIA Face Database, which includes 123 individuals with complex expressions. Experimental results show that our proposed method substantially improves the recognition performance under various facial expressions.