A model is presented, consonant with current views regarding the neurophysiology and psychophysics of motion perception, that combines the outputs of a set of spatiotemporal motion-energy filters to estimate image velocity. A parallel implementation computes a distributed representation of image velocity. A measure of image-flow uncertainty is formulated; preliminary results indicate that this uncertainty measure may be used to recognize ambiguity due to the aperture problem. The model appears to deal with the aperture problem as well as the human visual system since it extracts the correct velocity for some patterns that have large differences in contrast at different spatial orientations.
ASJC Scopus subject areas
- Computer Vision and Pattern Recognition
- Artificial Intelligence