Abstract
In this paper we propose a template matching approach to address the pose problem in face verification, which neither synthesizes the face image, nor builds a model of the face image. Template matching is performed using edginess-based representation of face images. The edginess-based representation of face images is computed using one-dimensional (1-D) processing of images. An approach is proposed based on autoassociative neural network (AANN) models to verify the identity of a person using score obtained from template matching.
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Sao, A.K., Yegnanaarayana, B. (2006). Template Matching Approach for Pose Problem in Face Verification. In: Gunsel, B., Jain, A.K., Tekalp, A.M., Sankur, B. (eds) Multimedia Content Representation, Classification and Security. MRCS 2006. Lecture Notes in Computer Science, vol 4105. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11848035_27
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DOI: https://doi.org/10.1007/11848035_27
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-39392-4
Online ISBN: 978-3-540-39393-1
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