Motion-Clouds

An open-source vision-science tool for the auto-regressive generation of dynamic stochastic textures Motion Clouds
Motion Clouds are a generative model for naturalistic visual stimulation that offer full parametric control and more naturalism than …
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Speed-Selectivity in Retinal Ganglion Cells is Sharpened by Broad Spatial Frequency, Naturalistic Stimuli
Motion detection represents one of the critical tasks of the visual system and has motivated a large body of research. However, it …
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Speed-Selectivity in Retinal Ganglion Cells is Sharpened by Broad Spatial Frequency, Naturalistic Stimuli
Bayesian Modeling of Motion Perception using Dynamical Stochastic Textures
A common practice to account for psychophysical biases in vision is to frame them as consequences of a dynamic process relying on …
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Bayesian Modeling of Motion Perception using Dynamical Stochastic Textures
How the dynamics of human smooth pursuit is influenced by speed uncertainty
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Voluntary tracking the moving clouds : Effects of speed variability on human smooth pursuit
The properties of motion processing for driving smooth eye movements have bee investigated using simple, artificial stimuli such as …
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Open Science
To enable the dissemination of the knowledge that is produced in our lab, we share all source code with open source licences.
Open Science
Voluntary tracking the moving clouds : Effects of speed variability on human smooth pursuit
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Voluntary tracking the moving clouds : Effects of speed variability on human smooth pursuit
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Voluntary tracking the moving clouds : Effects of speed variability on human smooth pursuit
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A Mathematical Account of Dynamic Texture Synthesis for Probing Visual Perception
See a followup in Jonathan Vacher, Andrew Isaac Meso, Laurent U Perrinet, Gabriel Peyré (2018). Bayesian Modeling of Motion Perception using Dynamical Stochastic Textures. Neural Computation. PDF Cite DOI URL arXiv
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Biologically Inspired Dynamic Textures for Probing Motion Perception
Talk @ NeurIPS: https://neurips.cc/Conferences/2015/Schedule?showEvent=5418 See a followup in Jonathan Vacher, Andrew Isaac Meso, Laurent U Perrinet, Gabriel Peyré (2018). Bayesian Modeling of Motion Perception using Dynamical Stochastic Textures. Neural Computation.
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Biologically Inspired Dynamic Textures for Probing Motion Perception
Beyond simply faster and slower: exploring paradoxes in speed perception
Estimating object speed in visual scenes is a critical part of perception. While various aspects of speed computation including …
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The characteristics of microsaccadic eye movements varied with the change of strategy in a match-to-sample task
Under natural viewing conditions, large eye movements are interspace by small eye movements (microsaccade). Recent works have shown …
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Dynamic Textures For Probing Motion Perception
This work extends the MotionClouds dynamic texture model testing aspects of its parametrization with an application in psychophysics.
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How and why do image frequency properties influence perceived speed?
Humans are able to interact successfully with moving objects in our dynamic world and the visual system effi ciently performs the …
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Measuring speed of moving textures: Different pooling of motion information for human ocular following and perception
The visual system does not process information instantaneously, but rather integrates over time. Integration occurs both for stationary …
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Pattern discrimination for moving random textures: Richer stimuli are more difficult to recognize
In order to analyze the characteristics of a rich dynamic visual environment, the visual system must integrate information collected at …
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Pattern discrimination for moving random textures: Richer stimuli are more difficult to recognize
MotionClouds: Model-based stimulus synthesis of natural-like random textures for the study of motion perception
2012-03-22
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Motion Clouds: Model-based stimulus synthesis of natural-like random textures for the study of motion perception
Choosing an appropriate set of stimuli is essential to characterize the response of a sensory system to a particular functional …
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Motion Clouds: Model-based stimulus synthesis of natural-like random textures for the study of motion perception
Effect of image statistics on fixational eye movements
Under natural viewing conditions, small movements of the eyes prevent the maintenance of a steady direction of gaze. It is unclear how …
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Measuring speed of moving textures: Different pooling of motion information for human ocular following and perception.
To measure speed and direction of moving objects, the cortical motion system pools information across different spatiotemporal …
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More is not always better: dissociation between perception and action explained by adaptive gain control
Moving objects generate motion information at different scales, which are processed in the visual system with a bank of spatiotemporal …
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More is not always better: dissociation between perception and action explained by adaptive gain control
Pattern discrimination for moving random textures: Richer stimuli are more difficult to recognize
In order to analyze the characteristics of a rich dynamic visual environment, the visual system must integrate information collected at …
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Edge statistics in natural images versus laboratory animal environments: implications for understanding lateral connectivity in V1
Oriented edges in images of natural scenes tend to be aligned in collinear or co-circular arrangements, with lines and smooth curves …
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Role of homeostasis in learning sparse representations
Neurons in the input layer of primary visual cortex in primates develop edge-like receptive fields. One approach to understanding the …
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Role of homeostasis in learning sparse representations
Different pooling of motion information for perceptual speed discrimination and behavioral speed estimation
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Dynamics of distributed 1D and 2D motion representations for short-latency ocular following
Integrating information is essential to measure the physical 2D motion of a surface from both ambiguous local 1D motion of its …
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Dynamics of distributed 1D and 2D motion representations for short-latency ocular following
Dynamical Neural Networks: modeling low-level vision at short latencies
The machinery behind the visual perception of motion and the subsequent sensori-motor transformation, such as in ocular following …
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Sparse Approximation of Images Inspired from the Functional Architecture of the Primary Visual Areas
relies on log-Gabor filters: Sylvain Fischer, Filip Šroubek, Laurent U Perrinet, Rafael Redondo, Gabriel Cristóbal (2007). Self-Invertible 2D Log-Gabor Wavelets. International Journal of Computer Vision. PDF Cite DOI Code URL Schematic structure of the primary visual cortex implemented in the present study.
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Sparse Approximation of Images Inspired from the Functional Architecture of the Primary Visual Areas