Joint Decision Making on Two Perception Systems Using Diversity Rank-Score Function Graph

Joint decision making on multiple visual perception systems have been studied extensively. However, the issues of what to choose (single decision or combination of more than one decision) and how to combine (average, weighted average, score, rank, or other fusion techniques) remain a challenging problem, even in the case of two systems. In this paper, we utilize the combinatorial fusion approach which treats a perception system, in this case human perception, as a scoring system and uses the notion of cognitive diversity to measure the dissimilarity of a pair of scoring patterns (or behavior). In particular, a diversity rank-score function graph is used as a visualization tool to decide which pairs of systems are good candidates to combine. Our work provides a general framework for joint decision making on visual perception systems and a powerful visualization tool for the combination of pairs of decision makers.

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