Abstract
In this paper, we propose using adaptive pixel/patch-based stereo matching for 2D face recognition. We don’t perform 3D reconstruction but define a measure of the similarity of two 2D face images. After rectifying the two images by epipolar geometry, we match them using the similarity for face recognition. The proposed approach has been tested on the CMU PIE and FERET database and demonstrates superior performance compared to existing methods in real-world situations including changes in pose and illumination.
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Liu, R., Feng, W., Zhu, M. (2013). Adaptive Pixel/Patch-Based Stereo Matching for 2D Face Recognition. In: Wilson, R., Hancock, E., Bors, A., Smith, W. (eds) Computer Analysis of Images and Patterns. CAIP 2013. Lecture Notes in Computer Science, vol 8047. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40261-6_20
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DOI: https://doi.org/10.1007/978-3-642-40261-6_20
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-40260-9
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