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Author Mavrinac, A. ♦ Shawky, A. ♦ Xiang Chen
Source IEEE Xplore Digital Library
Content type Text
Publisher Institute of Electrical and Electronics Engineers, Inc. (IEEE)
File Format PDF
Copyright Year ©2008
Language English
Subject Domain (in DDC) Computer science, information & general works ♦ Special computer methods
Subject Keyword Pixel ♦ Three dimensional displays ♦ Training ♦ Cameras ♦ Classification algorithms ♦ Shape ♦ Stereo vision
Abstract Once the human vision system has seen a 3D object from a few different viewpoints, depending on the nature of the object, it can generally recognize that object from new arbitrary viewpoints. This useful interpolative skill relies on the highly complex pattern matching systems in the human brain, but the general idea can be applied to a computer vision recognition system using comparatively simple machine learning techniques. An approach to the recognition of 3D objects in arbitrary pose relative the the vision equipment given only a limited training set of views is presented. This approach involves computing a disparity map using stereo cameras, extracting a set of features from the disparity map, and classifying it via a fuzzy associative map to a trained object.
ISBN 9781424418183
ISSN 10987584
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research ♦ Reading
Education Level UG and PG
Learning Resource Type Article
Publisher Date 2008-06-01
Publisher Place China
Rights Holder Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Size (in Bytes) 303.04 kB
Page Count 6
Starting Page 710
Ending Page 715


Source: IEEE Xplore Digital Library