Abstract
In this paper, a new method is proposed to estimate the accurate pose of face images. A face image collection device is designed to collect face image with accurate pose. Principle Component Analysis (PCA) is used to set up the eigenspace of face pose, then a fuzzy C-means clustering method is applied to divide the train samples into several classes, and to decide the centers of the classes. When a face image is presented to our system, we first project the image into the eigenspace, then the subordinate degree of the input face image to each class is calculated, finally the pose of the input face image is calculated combining the subordinate degrees. Experiments show that the proposed method can effectively estimate the accurate pose of face image.
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Du, C., Su, G. (2004). Face Pose Estimation Based on Eigenspace Analysis and Fuzzy Clustering. In: Yin, FL., Wang, J., Guo, C. (eds) Advances in Neural Networks - ISNN 2004. ISNN 2004. Lecture Notes in Computer Science, vol 3174. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-28648-6_65
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DOI: https://doi.org/10.1007/978-3-540-28648-6_65
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-22843-1
Online ISBN: 978-3-540-28648-6
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