Human eye movements are optimal for face recognition M Peterson, M P Eckstein |
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Department of Psychological & Brain Sciences, University of California, Santa Barbara, CA, United States
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| When identifying faces humans initially look towards the eyes. Unknown is whether this behavior is solely a by-product of socially important eye movement behavior (i.e., good eye contact) and the extraction of information about gaze direction, or whether the saccades have functional importance in basic perceptual tasks. Here, we propose that gaze behavior while determining a person’s identity, emotional state, or gender can be explained as an adaptive brain strategy to learn eye movement plans that optimize performance in these evolutionarily important perceptual tasks. We show that humans move their eyes to locations that maximize perceptual performance determining the identity, gender, and emotional state of a face, with fixations away from these preferred points resulting in significant degradation in perceptual performance. These optimal fixation points, which vary moderately across tasks, are correctly predicted by a Bayesian ideal observer that integrates information optimally across the face but is constrained by the decrease in resolution and sensitivity from the fovea towards the visual periphery (foveated ideal observer). Neither a model that disregards the foveated nature of the visual system and makes fixations on the local region with maximal information, nor a model that makes center-of-gravity fixations correctly predict human eye movements. These results suggest that the human visual system optimizes face recognition performance through guidance of eye movements. |
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