= PDF Reprint, = BibTeX entry, = Online Abstract
V. Navalpakkam, L. Itti, Optimal cue selection strategy, In: Advances in Neural Information Processing Systems, Vol. 19 (NIPS*2005), pp. 987-994, Cambridge, MA:MIT Press, 2006. [2005 acceptance rate: 24%] (Cited by 29)
Abstract: Survival in the natural world demands the selection of relevant visual cues to rapidly and reliably guide attention towards prey and predators in cluttered environments. We investigate whether our visual system selects cues that guide search in an optimal manner. We formally obtain the optimal cue selection strategy by maximizing the signal to noise ratio (SNR) between a search target and surrounding distractors. This optimal strategy successfully accounts for several phenomena in visual search behavior, including the effect of target-distractor discriminability, uncertainty in target's features, distractor heterogeneity, and linear separability. Furthermore, the theory generates a new prediction, which we verify through psychophysical experiments with human subjects. Our results provide direct experimental evidence that humans select visual cues so as to maximize SNR between the targets and surrounding clutter.
Themes: Computational Modeling, Model of Bottom-Up Saliency-Based Visual Attention, Model of Top-Down Attentional Modulation, Human Psychophysics
Copyright © 2000-2007 by the University of Southern California, iLab and Prof. Laurent Itti.
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