Connectionist robot motion planning: a neurally-inspired approach to visually-guided reaching
Connectionist robot motion planning: a neurally-inspired approach to visually-guided reaching
Using local models to control movement
Advances in neural information processing systems 2
The development of perceptual integration in visual robots
The development of perceptual integration in visual robots
What can be seen in three dimensions with an uncalibrated stereo rig
ECCV '92 Proceedings of the Second European Conference on Computer Vision
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Facing the competing demands for wider field of view and higher spatial resolution, computer vision will evolve toward greater use of foveal sensors and frequent camera movements. Integration of visual information across movements becomes a fundamental problem. We show that integration is possible using a biologically-inspired representation we call the visual-motor calibration map. The map is a memory-based model of the relationship between camera movements and corresponding pixel locations before and after any movement. The map constitutes a self-calibration that can compensate for non-uniform sampling, lens distortion, mechanical misalignments, and arbitrary pixel reordering. Integration takes place entirely in a retinotopic frame, using a short-term, predictive visual memory.