Journal of Pattern Recognition Research

In conventional still face recognition techniques, any query image is always classified to one of the face classes irrespective of whether the query image is a face or not. Most of the recognition algorithms are dissimilarity based, and one needs to put a proper threshold on the dissimilarity value for the sake of classification. In this paper, we have introduced a novel thresholding technique for classification for the video-to- video face frames. The theoretical formulation of the thresholding technique and its utility are demonstrated on each of the probe videos for still-to-video and video-to-video set. The proposed threshold selection is based on statistical method of set estimation and is guided by minimal spanning tree. It has been found that the proposed class specific threshold technique performs better than the other methods of threshold selection for videos.