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Author Suter, D.
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 ♦ Data processing & computer science
Subject Keyword Computers ♦ Computer vision ♦ Fitting ♦ Editorials ♦ Australia ♦ Data mining ♦ Multimedia communication
Abstract Summary form only given. Computer vision (the study of extracting information from images that includes robot vision, smart video surveillance, multi-media image search, camera-based human computer interfaces, etc.) deals with very large data rates: but it generally also has to contend with high-dimensional data and incomplete data and noise. The basic tools underpinning much of contemporary computer vision research: clustering, large (and possibly incomplete) matrix factorization, regression/model fitting, manifold learning etc.; are tools common to many other branches of computing. In this article, the author draw upon examples from his own research work to outline recent advances in dealing with high-dimensional data. Illustrative applications is given from computer vision problems (with some links made to other application areas).
Description Author affiliation: Dept. of Electr. & Comput. Syst. Eng., Monash Univ., Clayton, VIC (Suter, D.)
ISBN 9781424423576
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research ♦ Reading
Education Level UG and PG
Learning Resource Type Article
Publisher Date 2008-07-08
Publisher Place Australia
Rights Holder Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Size (in Bytes) 76.98 kB
Page Count 1
Starting Page 1
Ending Page 1


Source: IEEE Xplore Digital Library