August 2010
Volume 10, Issue 7
Free
Vision Sciences Society Annual Meeting Abstract  |   August 2010
Implicit Learning of Background Texture while Learning to Break Camouflage
Author Affiliations
  • Xin Chen
    Brain and Behavior Discovery Institute and Vision Discovery Institute, Medical College of Georgia, Augusta, GA
  • Jay Hegdé
    Brain and Behavior Discovery Institute and Vision Discovery Institute, Medical College of Georgia, Augusta, GA
    Department of Ophthalmology, Medical College of Georgia, Augusta, GA
Journal of Vision August 2010, Vol.10, 1114. doi:10.1167/10.7.1114
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      Xin Chen, Jay Hegdé; Implicit Learning of Background Texture while Learning to Break Camouflage. Journal of Vision 2010;10(7):1114. doi: 10.1167/10.7.1114.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

It can be difficult to recognize a visual object camouflaged against its background, even when the object is familiar and is ‘in plain sight’. However, the ability of the visual system to break camouflage can be improved with training. What the visual system learns during such training remains unclear. We hypothesized that learning to break camouflage involves learning, however implicitly, the statistical properties of the background, because this information is computationally helpful in breaking camouflage. To test this hypothesis, we synthesized a large number of novel instances of familiar natural textures (e.g., pebbles) using the texture synthesis algorithm of Portilla and Simoncelli (2000). We created novel camouflaged visual scenes by camouflaging a familiar object (face) against each instance of synthesized texture. We used some of these images to train normal adult human subjects to break camouflage using a two-alternative forced-choice detection paradigm (i.e., target present or absent), until subjects reached a criterion performance of d′ ≥ 1.5. We tested the detection performance before and after the training using previously unseen instances of the same texture. We found that the detection performance of the subjects was significantly better after the training relative to the performance before the training (e.g., d′ of 0.5 before training vs. 1.5 after training for a typical subject), indicating that the exposure to a given texture improved camouflage breaking in novel instances of the texture. Importantly, detection performance also improved for unfamiliar objects (e.g., ‘digital embryos’) that the subjects did not encounter during training, suggesting that the transfer of learning was not dependent on learning of the target per se. Moreover, the transfer of background learning was not specific to a given texture. Together, our results indicate the subjects can implicitly learn the background textures of camouflaged scenes even when not explicitly required to learn it.

Chen, X. Hegdé, J. (2010). Implicit Learning of Background Texture while Learning to Break Camouflage [Abstract]. Journal of Vision, 10(7):1114, 1114a, http://www.journalofvision.org/content/10/7/1114, doi:10.1167/10.7.1114. [CrossRef]
Footnotes
 Supported by Medical College of Georgia.
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