Abstract
To overcome the crucial problem of illumination, facial expression and pose variations in 2D face recognition, a novel algorithm is proposed by fusing global feature based on depth images and local facial feature based on Gabor filters. These two features are fused by residual combined with collaborative representation. Firstly, this approach extracts Gabor and Global feature from 3D depth images, then fuses two features via collaborative representation algorithm. The fused residuals serve as ultimate difference metric. Finally, the minimum fused residual corresponds to correct subject. Extensive experiments on CIS and Texas databases verify that the proposed algorithm is effective and robust.
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Zang, H., Zhan, S., Zhang, M., Zhao, J., Liang, Z. (2014). 3D Face Recognition by Collaborative Representation Based on Face Feature. In: Sun, Z., Shan, S., Sang, H., Zhou, J., Wang, Y., Yuan, W. (eds) Biometric Recognition. CCBR 2014. Lecture Notes in Computer Science, vol 8833. Springer, Cham. https://doi.org/10.1007/978-3-319-12484-1_20
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DOI: https://doi.org/10.1007/978-3-319-12484-1_20
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-12483-4
Online ISBN: 978-3-319-12484-1
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