Joint decision making in visual cognition using Combinatorial Fusion Analysis

Cognitive decision making based on visual sensory input has been a topic of recently increased interest. Using data acquired from the observation of pairs of human subjects, three currently discussed strategies for joint decision making are evaluated. In addition, Combinatorial Fusion Analysis (CFA), a framework which has proven effective for the optimization of multiple evaluation methods in other computational domains including bioinformatics, target tracking, and information retrieval, is applied to the data obtained herein. It is demonstrated that Combinatorial Fusion Analysis is useful in the study of visual cognition. Our results exhibit a new method to better analyze and make joint decisions in visual cognition using Combinatorial Fusion Analysis.