Abstract
Visual decision-making involving pairs of individuals tasked with determining the location of an object is a cognitive process combining independent systems together. Although it has been observed that combined systems can improve each of the individual systems, it remains a challenging problem to determine why and how this will occur. In this paper, we use Combinatorial Fusion Analysis (CFA) as a methodology through which we can effectively combine the decisions of two independent visual cognition systems. An experiment with 20 trials is performed in which participants are tasked with determining an object location, and stating the uncertainty factor for their decision. Our results demonstrate that the combination of two visual cognition systems using CFA can match or improve the performance of each individual system only if the pair of systems perform relatively well and are cognitively diverse.
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Mulia, D.A., Vergara, A., Skelsey, C.R., Yao, L., Hsu, D.F. (2014). When Are Two Visual Cognition Systems Better Than One?. In: Ślȩzak, D., Tan, AH., Peters, J.F., Schwabe, L. (eds) Brain Informatics and Health. BIH 2014. Lecture Notes in Computer Science(), vol 8609. Springer, Cham. https://doi.org/10.1007/978-3-319-09891-3_4
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DOI: https://doi.org/10.1007/978-3-319-09891-3_4
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