Motion-based prediction is sufficient to solve the aperture problem

a vision@UCL seminar

Time
Thursday, 12th January, 5pm
Location

Malet Place Eng Bldg 1.03 (first floor). Route from Russel square tube station.

Slides
• Laurent Perrinet, Guillaume S. Masson. Motion-based prediction is sufficient to solve the aperture problem. Neural Computation, 2012.

•  A predictive sequence is essential in resolving the aperture problem. The sequence in which a set of local motion is shown is essential for the detection of global motion. we replicate here the experiments by Scott Watamaniuk and colleagues. They have shown behaviourally that a dot in noise is much more detectable when it follows a coherent trajectory, up to an order of magnitude of 10 times what would be predicted by the local components of the trajectory. (Left) In this first movie we observe white noise and at first sight, no information is detectable. In fact, there is a dot moving along some smooth linear trajectory, but we broke this trajectory into eight equal parts and shuffled their order in the movie. (Right) if we re-arrange these local motions to be compatible with a predictive sequence, it is much easier to see the dot (from left to right in the top 25% line of the image, a smooth, slow pursuit helps to catch it). This simple experiment shows that, even if local motion is similar in both movies, a coherent trajectory is more easy to track. Obviously, we may thus conclude that the whole trajectory is more that its individual parts, and that the independence hypothesis does not hold if we want to account for the predictive information in input sequences such as seems to be crucial for the AP.

reference

• Laurent Perrinet. Motion-based prediction is sufficient to solve the aperture problem, URL . In Vision@UCL seminar - Thursday, 12th January, 5pm, 2012 abstract.

 This work was supported by European Union project Number FP7-269921, "BrainScales".

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