NDLI: Weighted Subspace Distance and Its Applications to Object Recognition and Retrieval With Image Sets

Content Provider	IEEE Xplore Digital Library
Author	Fei Li Qionghai Dai Wenli Xu Guihua Er
Copyright Year	1994
Abstract	We address the problem of measuring the distance between two subspaces, each of which is spanned by an image set. In the existing methods, only the orthonormal basis is used to represent the subspace. However, the images are usually distributed in a limited area, rather than the whole subspace. Therefore, the characteristics of the distribution should also be considered. In this letter, a weighted subspace distance (WSD) is proposed, in which the principal component values of the data set are adopted to calculate the weights. Experimental results on object recognition and retrieval with image sets demonstrate the effectiveness of our proposal.
Sponsorship	IEEE Signal Processing Society
Starting Page	227
Ending Page	230
Page Count	4
File Size	197840
File Format	PDF
ISSN	10709908
Volume Number	16
Issue Number	3
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-03-01
Publisher Place	U.S.A.
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Object recognition Image retrieval Erbium Proposals Computer vision Video sequences Computer displays Lighting Parametric statistics Distribution functions subspace distance object retrieval principal angles principle component analysis
Content Type	Text
Resource Type	Article
Subject	Applied Mathematics Electrical and Electronic Engineering Signal Processing

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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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