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CALL FOR PAPERS
Computer Vision and Image Understanding
Special Issue on Similarity Matching in Computer Vision and Multimedia
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Guest Editors:
Thomas S. Huang, University of Illinois at Urbana-Champaign, USA
Michael Lew, Leiden University, The Netherlands
Nicu Sebe, University of Amsterdam, The Netherlands
Qi Tian, University of Texas at San Antonio, USA
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URL: http://www.cs.utsa.edu/~qitian/cfp_cviu.htm
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Important dates:
Manuscript Submission: October 1, 2006
Acceptance Notification: February 15, 2007
Final Manuscript Due: April 15, 2007
Special Issue to Publisher: June 15, 2007
Expected Publication Date: Late 2007
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Submission Procedure
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Papers should be full journal length versions of the conference/workshop
paper with analysis and evaluation appropriate for journal publication.
Submissions should follow the guidelines set out by CVIU. All papers
should be submitted via the CVIU web-site with Article Type 'Special
Issue: Similarity Matching' http://ees.elsevier.com/cviu/
All papers will be peer reviewed following the CVIU reviewing procedures.
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Summary
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Comparing two images, or an image and a model, is the fundamental
operation for any retrieval systems. The similarity matching of two images
can reside in the hierarchical levels from pixel-by-pixel level, feature
space level, object level, and semantic level. In most systems of
interest, a simple pixel-by-pixel comparison won't do: the difference that
we determine must bear some correlation with the perceptual difference of
the two images or with the difference between two adequate semantics
associated to the two images. Similarity matching techniques are developed
mostly for recognition of objects under several conditions of the
distortion while similarity measures, on the other hand, are used in
applications like image databases. Matching and dissimilarity measurement
are not seldom based on the same techniques, but they differ in emphasis
and applications.
In recent years, there are an increasing number of papers and people in
workshops like Multimedia Information Retrieval (MIR), and major
conference like CVPR or CIVR addressing the similarity matching and
similarity measurement issues. The role of this special issue is to fill
the need of a comprehensive overview of the new approaches and advances of
similarity matching under the broad perspective of computer vision. It is
hoped that such a systematic and up-to-date overview of the field,
including tutorials to well established or new techniques, can bring the
awareness and applications of similarity matching closer to the general
multimedia community.
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Scope
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The scope of this special issue is to cover all aspects of similarity
matching in computer vision and multimedia. Topics of interest include
(but are not limited to):
Similarity matching in content-based image retrieval
Similarity matching in video analysis and retrieval
Similarity matching in image registration
Multimodal similarity matching
Change detection, e.g., audio, video, web documents, using similarity measure
Similarity search on the web
Content identification, e.g., copyright violation, digital right management
Quantitative measures and evaluation of the similarity search
Clustering analysis and grouping
Embedding methods for similarity search (e.g. image, DNA, documents)
Similarity metrics and invariant analysis
Psychovisual and human-perceptual similarity measures
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Contacts
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Please address all correspondences regarding this special issue to the
Guest Editors Dr. Thomas S. Huang (huang@ifp.uiuc.edu), Dr. Michael Lew
(mlew@liacs.nl), Dr. Nicu Sebe (nicu@science.uva.nl), and Dr. Qi Tian
(qitian@cs.utsa.edu)
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Qi Tian
Assistant Professor, Ph.D. Office: 3.02.13 SB
Department of Computer Science Phone: (210) 458-5165
University of Texas Fax: (210) 458-4437
6900 N. Loop 1604 West E-mail: qitian@cs.utsa.edu
San Antonio, TX 78249 http://www.cs.utsa.edu/~qitian
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