@inproceedings{2a0976620052413185e963bebc610640,
title = "A novel video face clustering algorithm based on divide and conquer strategy",
abstract = "Video-based face clustering is a very important issue in face analysis. In this paper, a framework for video-based face clustering is proposed. The framework contains two steps. First, faces are detected from videos and divided into subgroups using temporal continuity information and SIFT (Scale Invariant Feature Transform) features. Second, the typical samples are selected from these subgroups in order to remove some non-typical faces. A similarity matrix is then constructed using these typical samples in the subgroups. The similarity matrix is further processed by our method to generate the face clustering results of that video. Our algorithm is validated using the SPEVI datasets. The experiments demonstrated promising results from our algorithm.",
keywords = "face clustering, similarity measure, subgroup",
author = "Gaopeng Gou and Di Huang and Yunhong Wang",
year = "2012",
doi = "10.1007/978-3-642-32695-0\_7",
language = "英语",
isbn = "9783642326943",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
pages = "53--63",
booktitle = "PRICAI 2012",
note = "12th Pacific Rim International Conference on Artificial Intelligence, PRICAI 2012 ; Conference date: 03-09-2012 Through 07-09-2012",
}