Partial face recognition: An alignment free approach
Many approaches have been developed for holistic face recognition with impressive performance. However, few studies have addressed the question of how to recognize an arbitrary image patch of a holistic face. In this paper we address this problem of partial face recognition. Partial faces frequently appear in unconstrained image capture environments, particularly when faces are captured by surveillance cameras or handheld devices (e.g. mobile phones). The proposed approach adopts a variable-size description which represents each face with a set of keypoint descriptors. In this way, we argue that a probe face image, holistic or partial, can be sparsely represented by a large dictionary of gallery descriptors. The proposed method is alignment free and we address large-scale face recognition problems by a fast filtering strategy. Experimental results on three public domain face databases (FRGCv2.0, AR, and LFW) show that the proposed method achieves promising results in recognizing both holistic and partial faces.