Abstract
This paper presents a single sample per person (SSPP)-based face recognition method. Based on the Discriminative Multi-manifold Analysis (DMMA), we propose an accelerative face recognition method which consists of three modules. First, for one person one training image sample, we use a modified of K-means method to cluster two groups of people. Second, we divide the face images into non-overlapping local patches and apply DMMA. Third, we repeat the previous two steps to obtain the binary tree projection matrix of fast DMMA. In the experiments, we test the AR database and FERET database to verify the effectiveness of SSPP-based fast DMMA face recognition process in both accuracy and speed.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
