This paper describes a novel three-dimensional (3D) face recognition method when the head pose varies severely. Given an unknown 3D face, we extract several invariant facial features based on the facial geometry. We perform a Error Compensated Singular Value Decomposition (EC-SVD) for 3D face recognition. The novelty of the proposed EC-SVD procedure lies in compensating for the error for each rotation axis accurately. When the pose of a face is estimated, we propose a novel two-stage 3D face recognition algorithm. We first select face candidates based on the 3D-based nearest neighbor classifier and then the depth-based template matching is performed for final recognition. From the experimental results, less than a 0.2 degree error in average has been achieved for the 3D head pose estimation and all faces are correctly matched based on our proposed method. © Springer-Verlag 2004.
CITATION STYLE
Song, H., Yang, U., & Sohn, K. (2004). 3D face recognition under pose varying environments. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2908, 333–347. https://doi.org/10.1007/978-3-540-24591-9_25
Mendeley helps you to discover research relevant for your work.