Face recognition based on non-local similarity dictionary

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.