Neural Dynamics of Motion Segmentation and Grouping
Abstract
A neural network model of motion segmentation by visual cortex is de(cid:173) scribed. The model clarifies how preprocessing of motion signals by a Motion Oriented Contrast Filter (MOC Filter) is joined to long-range co(cid:173) operative motion mechanisms in a motion Cooperative Competitive Loop (CC Loop) to control phenomena such as as induced motion, motion cap(cid:173) ture, and motion aftereffects. The total model system is a motion Bound(cid:173) ary Contour System (BCS) that is computed in parallel with a static BCS before both systems cooperate to generate a boundary representation for three dimensional visual form perception. The present investigations clari(cid:173) fy how the static BCS can be modified for use in motion segmentation prob(cid:173) lems, notably for analyzing how ambiguous local movements (the aperture problem) on a complex moving shape are suppressed and actively reorga(cid:173) nized into a coherent global motion signal.
Cite
Text
Mingolla. "Neural Dynamics of Motion Segmentation and Grouping." Neural Information Processing Systems, 1990.Markdown
[Mingolla. "Neural Dynamics of Motion Segmentation and Grouping." Neural Information Processing Systems, 1990.](https://mlanthology.org/neurips/1990/mingolla1990neurips-neural/)BibTeX
@inproceedings{mingolla1990neurips-neural,
title = {{Neural Dynamics of Motion Segmentation and Grouping}},
author = {Mingolla, Ennio},
booktitle = {Neural Information Processing Systems},
year = {1990},
pages = {342-348},
url = {https://mlanthology.org/neurips/1990/mingolla1990neurips-neural/}
}