Abstract
With the increasing demand of surveillance camera-based applications, the very low resolution (VLR) problem occurs in many face application systems. Traditional two-step methods solve this problem through employing super-resolution (SR). However, these methods usually have limited performance because the target of SR is not absolutely consistent with that of face recognition. Moreover, time-consuming sophisticated SR algorithms are not suitable for real-time applications. To avoid these limitations, we propose a novel approach for VLR face recognition without any SR preprocessing. Our method based on the linear combination coefficients of non-local image patches is the same regardless of image resolutions inspired by the learning-based face SR method. Experimental results show that the proposed VLR face recognition method is high in recognition accuracy and robust in resolution variations.
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Liao, H., Lu, S., Chen, Q. (2014). Face Recognition Based on Non-local Similarity Dictionary. 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_7
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DOI: https://doi.org/10.1007/978-3-319-12484-1_7
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-12483-4
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