Innovative Sparse Representation Algorithms for Robust Face Recognition
In recent years, face recognition has been substantially studied both in the academic community and industry with many significant results achieved. The target of face recognition is to build systems which can perform automatic person identification or verification, when a digital image or a video frame sequence of that person is provided. In this paper, the authors propose two innovative and computationally efficient algorithms for robust face recognition, which extend the previous Sparse Representation-based Classification (SRC) algorithm proposed by Wright et al. (2009). The two new algorithms, which are designed for both batch and online modes, operate on matrix representation of images, as opposed to vector representation in SRC, to achieve efficiency whilst maintaining the recognition performance.