NDLI: On the convergence and applications of mean shift type algorithms

Content Provider	IEEE Xplore Digital Library
Author	Aliyari Ghassabeh, Y. Linder, T. Takahara, G.
Copyright Year	2012
Description	Author affiliation: Dept. of Math. & Stat., Math. & Eng. Program, Queen's Univ., Kingston, ON, Canada (Aliyari Ghassabeh, Y.; Linder, T.; Takahara, G.)
Abstract	Mean shift (MS) and subspace constrained mean shift (SCMS) algorithms are iterative methods to find an underlying manifold associated with an intrinsically low dimensional data set embedded in a high dimensional space. Although the MS and SCMS algorithms have been used in many applications related to information and signal processing, a rigorous study of their convergence properties is still missing. This paper aims to fill some of the gaps between theory and practice. We present theoretical results about convergence of the MS and SCMS algorithms. As well, we discuss potential applications of the SCMS algorithm as a preprocessing step for noisy source vector quantization and nonlinear dimensionality reduction with noisy observations.
Sponsorship	IEEE Montreal Sect.
Starting Page	1
Ending Page	5
File Size	804800
Page Count	5
File Format	PDF
ISBN	9781467314312
ISSN	08407789
e-ISBN	9781467314336
e-ISBN	9781467314329
DOI	10.1109/CCECE.2012.6334859
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-04-29
Publisher Place	Canada
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Noise measurement Kernel Convergence Vectors Vector quantization Signal processing algorithms Manifolds nonlinear dimensionality reduction Mean shift algorithm subspace constrained mean shift algorithm noisy source vector quantization
Content Type	Text
Resource Type	Article
Subject	Electrical and Electronic Engineering Hardware and Architecture

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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