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Dynamical texture synthesis to probe visual perception| old_uid | 15822 |
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| title | Dynamical texture synthesis to probe visual perception |
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| start_date | 2015/06/16 |
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| schedule | 14h30-16h30 |
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| online | no |
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| location_info | salle de conférence |
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| summary | In this talk, I will review statistical models of dynamical textures, targeting applications to computer graphics synthesis and stimulations to probe the visual cortex. I will focus in particular my attention to Gaussian texture models. Despite their simplicity, they are surprisingly effective at capturing micro-textural patterns and simple dynamics. These models can be parameterized as linear stochastic partial differential equations, which makes them easy to learn from exemplar videos and fast to synthesize on the fly. This also opens the door to both Fourier analysis (power-spectrum parameterization) and an interpretation as an infinite superposition of translated/rotated/scaled elementary "textons". Both interpretations are crucial to allow formalizing psychophysical studies in term of an optimal Bayesian observer. I will show how this explains some psychophysical findings about the influence of texture statistics to bias human speed discrimination (joint work with J. Vacher, L. Perrinet and A. Meso). |
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| responsibles | Citti, Nadal, Faugeras |
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