Abstract
In this paper we propose a new range-based face recognition for significant improvement in the recognition rate using an optimized stereo acquisition system. The optimized 3D acquisition system consists of an eyes detection algorithm, facial pose direction distinction, and principal component analysis (PCA). The proposed method is carried out in the YCbCr color space in order to detect the face candidate area. To detect the correct face, it acquires the correct distance of the face candidate area and depth information of eyes and mouth. After scaling, the system transfers the pose change according to the distance. The face is finally recognized by the optimized PCA for each area with the facial pose elements detected. Simulation results with face recognition rate of 95.83% (100cm) in the front and 98.3% with the pose change were obtained successfully. Therefore, proposed method can be used to obtain high recognition rate with an appropriate scaling and pose change according to the distance.
This research was supported by Korean Ministry of Science and Technology under the National Research Laboratory Project, Korean Ministry of Information and Communication under HNRC-ITRC program at Chung-Ang university supervised by IITA, and the Research Grant of Kwangwoon University in 2005.
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© 2005 Springer-Verlag Berlin Heidelberg
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Park, C., Park, S., Shin, J., Paik, J., Namkung, J. (2005). Face Recognition Using Optimized 3D Information from Stereo Images. In: Kamel, M., Campilho, A. (eds) Image Analysis and Recognition. ICIAR 2005. Lecture Notes in Computer Science, vol 3656. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11559573_127
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DOI: https://doi.org/10.1007/11559573_127
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-29069-8
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