Feature Selection in Interactive Face Retrieval

摘要：

In this paper, we introduce a novel perspective to feature selection in face retrieval, for the purpose of increasing the coherence in face similarity feedback, and hence narrowing the semantic gap between human and machine in face perception, and thus speeding up the interactive retrieval. The coherence is defined in previously established interactive face retrieval models and the feedback database of human users is built up for building or testing those models. Based on this coherence database, we propose a novel criterion function as the target function in feature selection to measure the coherence. Four feature selection algorithms have been adopted in comparison: the minimal-RedundancyMaximal-Relevance criterion (mRMR), the best individual (BI), the sequential forward selection (SFS), and the Plus-ι-Minus-r (ι-r). The ι-r algorithm proves to be better than the other three methods in feature selection for coherence. Experiments demonstrate that the proposed feature selection method could largely improve the interactive searching efficiency and face recognition rate in face databases.

关键词： feature selection coherence face interactive retrieval

作者: Wang Dai Yuchun Fang Binbin Hu

作者单位: School of Computer Engineering and Science Shanghai University Shanghai, China

会议类型: 国际会议

会议名称: 2011 4th International Congress on Image and Signal Processing(第四届图像与信号处理国际学术会议 CISP 2011)

会议地点: 上海

会议语种:英文

页码: 1379-1383

在线出版日期: 2011-10-15（万方平台首次上网日期，不代表论文的发表时间）