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Abstract

How does the visual system recognize a camouflaged object? Obviously, the brain cannot afford to learn all possible camouflaged scenes or target objects. However, it may learn the general statistical properties of backgrounds of interest, which would enable it to break camouflage by comparing the statistics of a background with a target versus the statistics of the same background without a target. To determine whether the brain uses this strategy, we digitally created novel camouflaged scenes that had only the general statistical properties of the background in common. When subjects learned to break camouflage, their ability to detect a camouflaged target improved significantly not only for previously unseen instances of a camouflaged scene, but also for scenes that contained novel targets. Moreover, performance improved even for scenes that did not contain an actual target but had the statistical properties of backgrounds with a target. These results reveal that learning backgrounds is a powerful, versatile strategy by which the brain can learn to break camouflage.

Keywords

perceptual learning object recognition vision cognitive processes

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Learning to Break Camouflage by Learning the Background

Abstract

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