Face Clustering in videos based on Spectral Clustering Techniques

摘要：

In this paper we propose a novel algorithm for face clustering using spectral graph clustering in order to split and merge a similarity graph. The proposed method makes use of the mutual information-based image similarity. Face clusters are formed based on spectral graph clustering in a two step process. We begin by partitioning the dataset into clusters. A novel adaptive way is proposed for spectral clustering. Then merge is performed using spectral graph clustering on the partitioned clusters, by considering merging only two clusters at a time. Experiments on various video databases containing actors’ facial images are conducted. The evaluation of the face clustering provided very good results.

作者: Christina Chrysouli Nicholas Vretos Ioannis Pitas

作者单位: Department of Informatics University of ThessalonikiThessaloniki, Greece 54124 Department of Informatics University of Thessaloniki Thessaloniki, Greece 54124

会议类型: 国际会议

会议名称: 第一届亚洲模式识别会议

会议地点: 北京

会议语种:英文

页码: 130-134

在线出版日期: 2011-11-28（万方平台首次上网日期，不代表论文的发表时间）