Face recognition and gender classification in personal memories

Face annotation is an important concept for personal memories retrieval. Using automatic face recognition to annotate and find people in those memories provides an improvement of a personal memories management system. However, its results are limited by the uncontrolled conditions inherent to personal memories. In this paper, we propose a face recognition method to address these limitations which includes techniques of skin detection and pose estimation. It is also proposed a gender classification method to provide more information about the detected faces. Experimental results are presented that show that these methods improve the overall performance of face recognition and gender classification in personal memories.