Video face naming using global sequence alignment

This paper explores the problem of automatically naming faces in TV series or films. A novel method is proposed to build association between the faces in the video and the names in the script by a global sequence alignment algorithm. We firstly build two heterogenous sequences: a face sequence and a name sequence. The elements of the two sequences are cluster labels, computed from the clustering process, and speaking names, respectively. Then the alignment of the two sequences is considered as a problem of surjection between the cluster set and the name set. The optimal solution is obtained by minimizing the Levenshtein Distance between the two sequences which is constrained by the temporal order information. Experiments on public videos demonstrate the effectiveness of our method.