NDLI: Indexing visual representations through the complexity map

Content Provider	IEEE Xplore Digital Library
Author	Dubuc, B. Zucker, S.W.
Copyright Year	1995
Description	Author affiliation: McGill Res. Centre for Intelligent Machines, McGill Univ., Montreal, Que., Canada (Dubuc, B.; Zucker, S.W.)
Abstract	In differential geometry curves are characterized as mappings from an interval to the plane. In topology curves are characterized as a Hausdorff space with certain countability properties. Neither of these definitions captures the role that curves play in vision, however, in which 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. Note that the map defining such curves is unknown, as is the proper way to represent them. We propose a formal complexity theory of curves appropriate for computational vision in general, and for problems like separating straight lines from jumbles in particular. The theory is applied to the problem of perceptual grouping.<>
Starting Page	142
Ending Page	149
File Size	773001
Page Count	8
File Format	PDF
ISBN	0818670428
DOI	10.1109/ICCV.1995.466794
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1995-06-20
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Indexing Image edge detection Hair Geometry Topology Complexity theory Computer vision Area measurement Length measurement Detectors
Content Type	Text
Resource Type	Article

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