@inbook{4d4b80d3d7ff4caabf264257e5d5e2b3,
title = "3D face recognition under pose varying environments",
abstract = "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.",
author = "Hwanjong Song and Ukil Yang and Kwanghoon Sohn",
year = "2004",
doi = "10.1007/978-3-540-24591-9_25",
language = "English",
isbn = "3540208275",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "333--347",
editor = "Kijoon Chae and Moti Yung",
booktitle = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
address = "Germany",
}