Two Stages of Curve Detection Suggest Two Styles of Visual Computation
- 1 March 1989
- journal article
- Published by MIT Press in Neural Computation
- Vol. 1 (1) , 68-81
- https://doi.org/10.1162/neco.1989.1.1.68
Abstract
The problem of detecting curves in visual images arises in both computer vision and biological visual systems. Our approach integrates constraints from these two sources and suggests that there are two different stages to curve detection, the first resulting in a local description, and the second in a global one. Each stage involves a different style of computation: in the first stage, hypotheses are represented explicitly and coarsely in a fixed, preconfigured architecture; in the second stage, hypotheses are represented implicitly and more finely in a dynamically constructed architecture. We also show how these stages could be related to physiology, specifying the earlier parts in a relatively fine-grained fashion and the later ones more coarsely.Keywords
This publication has 10 references indexed in Scilit:
- Corner detection in curvilinear dot groupingBiological Cybernetics, 1988
- Snakes: Active contour modelsInternational Journal of Computer Vision, 1988
- Analyzing oriented patternsComputer Vision, Graphics, and Image Processing, 1987
- The computational connection in vision: Early orientation selectionBehavior Research Methods, Instruments & Computers, 1986
- Contour, color and shape analysis beyond the striate cortexVision Research, 1985
- Selective Attention Gates Visual Processing in the Extrastriate CortexScience, 1985
- Stimulus Specific Responses from Beyond the Classical Receptive Field: Neurophysiological Mechanisms for Local-Global Comparisons in Visual NeuronsAnnual Review of Neuroscience, 1985
- On the Foundations of Relaxation Labeling ProcessesPublished by Institute of Electrical and Electronics Engineers (IEEE) ,1983
- On the optimal detection of curves in noisy picturesCommunications of the ACM, 1971
- Receptive fields, binocular interaction and functional architecture in the cat's visual cortexThe Journal of Physiology, 1962