
doi: 10.1007/bf00204665
pmid: 1958735
Energy filters are tuned to space-time frequency orientations. In order to compute velocity it is necessary to use a collection of filters, each tuned to a different space-time frequency. Here we analyze, in a probabilistic framework, the properties of the motion uncertainty. Its lower bound, which can be explicitly computed through the Cramér-Rao inequality, will have different values depending on the filter parameters. We show for the Gabor filter that, in order to minimize the motion uncertainty, the spatial and temporal filter sizes cannot be arbitrarily chosen; they are only allowed to vary over a limited range of values such that the temporal filter bandwidth is larger than the spatial bandwidth. This property is shared by motion sensitive cells in the primary visual cortex of the cat, which are known to be direction selective and are tuned to space-time frequency orientations. We conjecture that these cells have larger temporal bandwidth relative to their spatial bandwidth because they compute velocity with maximum efficiency, that is, with a minimum motion uncertainty.
Energy filters, Models, Neurological, Motion Perception, motion uncertainty, Gabor filter, Time, spatial bandwidth, Neural biology, Space Perception, space-time frequency orientations, Cramér-Rao inequality, Animals, Humans, temporal bandwidth, Computer Simulation, visual cortex, Mathematics, Visual Cortex
Energy filters, Models, Neurological, Motion Perception, motion uncertainty, Gabor filter, Time, spatial bandwidth, Neural biology, Space Perception, space-time frequency orientations, Cramér-Rao inequality, Animals, Humans, temporal bandwidth, Computer Simulation, visual cortex, Mathematics, Visual Cortex
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 4 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
