Abstract
In vision, curves can denote simple objects (such as a straight line), or complicated objects (such as a jumble of string). The difference between these situations is in part a measure of their complexity, and in part a measure of their dimensionality. Our goal is to develop a formal theory of curves appropriate for computational vision in general, and for problems like separating straight lines from strings in particular. The theory is applied to the problem of perceptual grouping.
Research supported by the AFOSR and NSERC. S.W.Z. is a Fellow of the Canadian Institut for Advanced Research.
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© 1995 Springer-Verlag Berlin Heidelberg
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Dubuc, B., Zucker, S.W. (1995). A complexity space for curve grouping. In: Hlaváč, V., Šára, R. (eds) Computer Analysis of Images and Patterns. CAIP 1995. Lecture Notes in Computer Science, vol 970. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-60268-2_277
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DOI: https://doi.org/10.1007/3-540-60268-2_277
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