Face Hierarchical Clustering with SIFT-Based Similarities

Abstract

In this paper, a face image hierarchical clustering method is proposed, which employs the scale invariant feature transform (SIFT) for extracting image features and further defines a novel measure of similarities between pairs of face images. Experiments show that the proposed hierarchical clustering method performs better than the other reported SIFT-based clustering approaches.