Theories and methodologies for representing and abstracting shape from visual information are a major concern in computational vision. Important contributions have been made on e.g. theories of dynamic shape, on the detection of salient structures like symmetries and discontinuities and also on the use of mathematical techniques of optimization and approximation.
Here we will survey some of these approaches and discuss what they make explicit and how that can be computed. In particular, we will consider such techniques in view of the figure-ground problem and the desirability of qualitative vs. quantitative descriptions.
KeywordsMachine Intelligence Error Criterion Shape Property Tangent Discontinuity Noise Sensitivity
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