FACE ANNOTATION FOR ONLINE PERSONAL VIDEOS USING COLOR FEATURE FUSION BASED FACE RECOGNITION

This paper proposes a novel weighted feature fusion in color face recognition (FR) to automatically annotate faces in personal videos. In the proposed FR method, multiple face images (belonging to the same subject) are clustered from a sequence of video frames. To facilitate a complementary effect on improving annotation performance, the grouped faces are combined using the proposed weighted feature fusion. In addition, we make effective use of facial color feature to cope with decrease in annotation performance due to a low-resolution face in personal videos. To evaluate the effectiveness of proposed FR method, more than 40,000 video frames for 10 real-world personal videos are collected from an existing online video sharing website. Experimental results show that the proposed FR method significantly improves annotation performance obtained using conventional grayscale image based FR methods.