Learning Saccadic Eye Movements Using Multiscale Spatial Filters
Rajesh P. N. Rao, Dana H. Ballard · 1994
We describe a framework for learning saccadic eye movements using a photometric representation of target points in natural scenes. The representation takes the form of a high-dimensional vector comprised of the responses of spatial filters at different orientations and scales. We first demonstrate the use of this response vector in the task of locating previously foveated points in a scene and subsequently use this property in a multisaccade strategy to derive an adaptive motor map for delivering accurate saccades. 1 Introduction There has been recent interest in the use of space-variant sensors in active vision systems for tasks such as visual search and object tracking [14]. Such sensors realize the simultaneous need for wide field-of-view and good visual acuity. One popular class of space-variant sensors is formed by log-polar sensors which have a small area near the optical axis of greatly increased resolution (the fovea) coupled with a peripheral region that witnesses a gradual l...