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Aude Oliva; High level visual ensemble statistics: Encoding the layout of visual space. Journal of Vision 2010;10(7):27. doi: 10.1167/10.7.27.
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© ARVO (1962-2015); The Authors (2016-present)
Visual scene understanding is central to our interactions with the world. Recognizing the current environment facilitates our ability to act strategically, for example in selecting a route for walking, anticipating where objects are likely to appear, and knowing what behaviors are appropriate in a particular context. In this talk, I will discuss a role for statistical, ensemble representations in scene and space representation. Ensemble features correspond to a higher-level description of the input that summarizes local measurements. With this ensemble representation, the distribution of local features can be inferred and used to reconstruct multiple candidate visual scenes that share similar ensemble statistics. Pooling over local measurements of visual features in natural images is one mechanism for generating a holistic representation of the spatial layout of natural scenes. Potentially, the richness of content and spatial volume in a scene can be at least partially captured using the compressed yet informative description of statistical ensemble representations.
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