Abstract
A novel color face recognition approach coined Fisher diagonal non-negative matrix factorization (Fisher-DNMF) is proposed in this paper. The approach employs block diagonal matrix to encode color information of different channels. Block diagonal constraint and Fisher discrimination constraint are imposed on the non-negative matrix factorization algorithm to factorize matrices of different channels simultaneously. And Fisher-DNMF algorithm is exploited to extract facial features. Nearest neighborhood classifier is adopted to identify color face samples. Experimental results on CVL and CMU PIE color face databases verify the effectiveness of the proposed approach.
Sign-in/Register to access full text options 
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.
