DynTex: A real-time generative model of dynamic naturalistic scenes from luminance textures

03 Sep 2025 in Publications

with A. I. Meso, N. Gekas, P. Mamassian, L. U. Perrinet and G. S. Masson.

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This paper presents DynTex, a real-time toolbox for generating controlled naturalistic dynamic textures. It grows out of the Motion Clouds framework and is meant for experiments that need richer motion stimuli than simple gratings while preserving precise parameter control.

1. Meso, A. I. et al. DynTex: A real-time generative model of dynamic naturalistic scenes from luminance textures. Journal of Vision 25, 2–2 (2025).

   @article{meso2025dyntex,
     title = {DynTex: A real-time generative model of dynamic naturalistic scenes from luminance textures},
     author = {Meso, Andrew I. and Vacher, Jonathan and Gekas, Nikos and Mamassian, Pascal and Perrinet, Laurent U. and Masson, Guillaume},
     journal = {Journal of Vision},
     volume = {25},
     number = {11},
     pages = {2--2},
     year = {2025},
     publisher = {The Association for Research in Vision and Ophthalmology}
   }
   

Overview

The toolbox exposes orientation, speed, and spatiotemporal frequency structure in a form that can be explored interactively, integrated with Psychtoolbox or PsychoPy, and rendered on the GPU in real time. The broader goal is to make naturalistic motion stimuli practical for psychophysics, neurophysiology, and computational modeling.