NDLI: Shape contexts enable efficient retrieval of similar shapes

Content Provider	IEEE Xplore Digital Library
Author	Mori, G. Belongie, S. Malik, J.
Copyright Year	2001
Description	Author affiliation: California Univ., Berkeley, CA, USA (Mori, G.)
Abstract	In this paper we demonstrate that a recently introduced shape descriptor, the "shape context", can be used to quickly prune a search for similar shapes. Our representation for a shape is a discrete set of n points sampled from its internal and external contours. For each of these points, the shape context is a histogram of the relative positions of the n - 1 remaining points. We present two methods for rapid shape retrieval: one that does comparisons based on a small number of shape contexts and another that uses vector quantization in the space of shape contexts. We verify the discriminative power of these methods with tests on the Columbia (COIL-100) 3D object database and the Snodgrass and Vanderwart line drawings. The shape context-based methods are shown to quickly produce an accurate shortlist of candidates suitable for a more exact matching engine in spite of pose variation and occlusion.
Sponsorship	IEEE Comput. Soc. Tech. Committee on Pattern Analysis & Machine Intelligence
File Size	780552
File Format	PDF
ISBN	0769512720
ISSN	10636919
DOI	10.1109/CVPR.2001.990547
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2001-12-08
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Shape Histograms Quantization Testing Databases Engines Face recognition Animals Humans Detectors
Content Type	Text
Resource Type	Article
Subject	Computer Vision and Pattern Recognition Software

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