Face Recognition Using Face-ARG Matching

Bo Gun Park, Kyoung Mu Lee, Sang Uk Lee

Abstract: In this paper, we propose a novel line feature-based face recognition algorithm. A face is represented by the face-ARG model, where all the geometric quantities and the structural information are encoded in an attributed relational graph (ARG) structure, then the partial ARG matching is done for matching face-ARG's. Experimental results demonstrate that the proposed algorithm is quite robust to various facial expression changes, varying illumination conditions and occlusion, even when a single sample per person is given.