An Attention-Based Decision Fusion Scheme for Multimedia Information Retrieval

In this paper, we proposed a novel decision fusion scheme based on the psychological observations on human beings' visual and aural attention characteristics, which combines a set of decisions obtained from different data sources or features to generate better decision result. Based on studying of the “heterogeneity” and “monotonicity” properties of certain types of decision fusion issues, a set of so-called Attention Fusion Functions are devised, which are able to obtain more reasonable fusion results than typical fusion schemes. Preliminary experiment on image retrieval shows the effectiveness of the proposed fusion scheme.

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