A bi-objective optimization model for interactive face retrieval

Authors:
Yuchun Fang;Qiyun Cai;Jie Luo;Wang Dai;Chengsheng Lou
Affiliations:
School of Computer Engineering and Science, Shanghai, China;School of Computer Engineering and Science, Shanghai, China;School of Computer Engineering and Science, Shanghai, China;School of Computer Engineering and Science, Shanghai, China;School of Computer Engineering and Science, Shanghai, China
Venue:
MMM'11 Proceedings of the 17th international conference on Advances in multimedia modeling - Volume Part II
Year:
2011

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Abstract

In this paper, based on Bayesian relevance feedback methods, we propose a novel interactive face retrieving model based on two objective functions, one is the Maximum a Posterior (MAP) and the other is maximization of mutual information. The proposed bi-objective optimization model aims at minimizing both the number of interactive iterations and the average length of iterations. Moreover, we deduce a top-bottom search algorithm to solve the proposed. Experiments with real testers prove that the proposed algorithm could largely improve the interactive searching efficiency in face databases.