Abstract
Recognizing human face is one of the most important part in biometrics. However, drastic change of facial pose makes it a difficult problem. In this paper, we propose linear pose transformation method in feature space. At first, we extracted features from input face image at each pose. Then, we used extracted features to transform an input pose image into its corresponding frontal pose image. The experimental results show that recognition rate with pose transformation is much better than the result without pose transformation.
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© 2004 Springer-Verlag Berlin Heidelberg
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Lee, HS., Kim, D. (2004). Pose Invariant Face Recognition Using Linear Pose Transformation in Feature Space. In: Sebe, N., Lew, M., Huang, T.S. (eds) Computer Vision in Human-Computer Interaction. CVHCI 2004. Lecture Notes in Computer Science, vol 3058. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24837-8_20
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DOI: https://doi.org/10.1007/978-3-540-24837-8_20
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-22012-1
Online ISBN: 978-3-540-24837-8
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