A Matlab implementation of Laurent Perrinet's (INT - CNRS) motion cloud spatio-temporal random textures.
Motion clouds are a class of random phase textures. Here they are implemented as dense mixtures of localized drifting gratings with random positions.
For a formal description see:
Sanz Leon et al., Motion clouds: model-based stimulus synthesis of natural-like random textures for the study of motion perception. J. Neurophysiol. 107:3217-3226, 2012.
For Laurent Perrinet's Python implementation see:
https://github.com/NeuralEnsemble/MotionClouds.git
Example usage:
import motionclouds.*
m = motioncloud(256,256,120); % 256 x 256 texels, 120 frames
% override default parameters
m.th = pi/3; % mean orientation (radians)
[m.Vx,m.Vy] = pol2cart(m.th,1.0); % mean horiz. and vert. speed
m.sf = 32/m.Nx; % mean spatial frequency (32 cycles per frame)
m.alpha = 1.0; % 1/f noise spectral density
m.contrast = 0.12; % contrast energy
m.method = 'ENERGY';
% generate the spatio-temporal image sequence
s = m.getSequence();
% preview it...
figure; colormap(gray(256));
for ii = 1:m.Nt % loop over frames
imagesc(s(:,:,ii); axis image
delay(0.020);
end
The example above produces a spatio-temporal texture, the first 5 frames of which look something like:
