July 2011 Newsletter July 2011 Newsletter

Welcome to the July edition of the IEEE-TCMC (Technical Committee
on Multimedia Computing) monthly mailing.

TCMC membership is officially determined by signing up with the IEEE
Computer Society either with your membership or later through:


TCMC home: http://www.computer.org/portal/web/tcmc

This month's topics include:

Several special issues with Visual Communication and Image
Representation (JVCI), Computer Vision and Image Understanding, and
IEEE Multimedia

Special Issue on Sparse Representations for Image and Video Analysis
Journal of Visual Communication and Image Representation (JVCI)

Sparse representation has gained popularity in the last few years as a
technique to reconstruct a signal with few training examples. This
reconstruction can be defined as adaptively finding a dictionary which
best represents the signal on sample bases. Sparse representation
establishes a more rigorous mathematical framework for studying
high-dimensional data and ways to uncover the structures of the data,
giving rise to a large repertoire of efficient algorithms. The sparse
representation has just been applied to visual analysis for few years,
while has shown its advantages in processing the visual information. Thus
it will have a great potential in this field. Sparse representation has
wide applications in image/video processing, analysis, and understanding,
such as denoising, deblurring, inpainting, compression, super-resolution,
detection, classification, recognition, and retrieval. Many approaches
based on sparse representation were proposed for these applications in the
past years, and showed the promising results. This special issue aims to
bring together the range of research efforts in sparse representation for
image/video processing, analysis, and understanding. The goals of this
special issue are threefold: (1) to introduce the advances of the theories
on sparse representation; (2) to survey the progress of the applications
of sparse representation in visual analysis; and (3) to discuss new sparse
representation based technologies that will be potentially impactful in
the image/video applications (primary results are needed).


The scope of this special issue is to cover all aspects that relate to
sparse representation for visual analysis. Topics of interest include,
but are not limited to the following:

The fundamental theories on sparse representation
Dictionary learning for sparse representation and modeling
The novel learning methods based on sparse representation
The applications of sparse representation in image/video denoising,
impainting, debluerring, compression, and super-resolution
Sparse representation for pattern recognition and classification
Sparse representation for image/video retrieval
Sparse reconstruction for medical imaging and radar imaging
Sparse component analysis and its application to blind source separation

Information for Authors

Authors should prepare their manuscript according to the Guide for Authors
available from the online submission page of the 'Journal of Visual
Communication and Image Representation' at http://ees.elsevier.com/jvci/.
When submitting via this page, please select "SparseRepresentations" as
the Article Type. Prospective authors should submit high quality, original
manuscripts that have not appeared, nor are under consideration, in any
other journals. All submissions will be peer reviewed following the JVCI
reviewing procedures.

Important Dates

Manuscript Submission Deadline: October 1, 2011
Notification of Acceptance/Rejection: January1, 2012
Final Manuscript Due to JVCI: April 1, 2012
Expected Publication Date: Fall 2012

Guest Editors

Jinhui Tang
Nanjing University of Science and Technology, China

Shuicheng Yan
National University of Singapore, Singapore

John Wright
Microsoft Research Asia, China

Qi Tian
University of Texas at San Antonio, USA

Yanwei Pang
Tianjin University, China

Edwige Pissaloux
Université Pierre et Marie Curie (UPMC- Paris 6), France

Large-Scale Multimedia Data Collections


Submission Deadline: 1 October 2011
Publication Issue: July-September 2012

Pivotal to many tasks in relation to multimedia research and development is
the availability of a sufficiently large data set and its corresponding
ground truth. Currently, most available data sets for multimedia research
are either too small, such as the Corel or Pascal data sets; too specific,
such as the Text Retrieval Conference Video (Trecvid) data set; or without
ground truth, such as the recent efforts by the Massachusetts Institute of
Technology and Microsoft Research Asia that gathered millions of Web images
for testing. While it's relatively easy to crawl and store a huge amount of
data, the creation of ground truth necessary to systematically train, test,
evaluate, and compare the performance of various algorithms and systems is a
major problem. For this reason, more and more research groups are
individually putting efforts into the creation of such corpus to carry out
research on large-scale data sets. There is a need to unify these individual
efforts into the creation of a unified Web-scale repository that would
benefit the entire multimedia research community.

The purpose of this special issue is to present and report on the
construction and analysis of large-scale multimedia data sets and resources,
and to provide a strong reference for multimedia researchers interested in
large-scale multimedia data sets. The issue will specifically address the
construction of data sets; the creation of ground truths; the sharing and
extending of such resources in terms results and analysis related to ground
truth, features, algorithms, and tools.

The IEEE MultiMedia special issue on large-scale multimedia data collections
solicits original papers that will be of interest for IEEE MultiMedia
readers. The list of possible topics includes, but is not limited to:

- Construction, unification, and evolution of corpus: the state of use, the
lessons learned, and their impact, scalability of results, and range of
- Framework for sharing of data sets, ground truths, features, algorithms,
and tools, as well as comparison and analysis of results.
- Large-scale corpus analysis techniques: knowledge mining from large-scale
multimedia corpus, optimization techniques on large-scale multimedia data
for efficiency, and techniques for large-scale, content-based multimedia
- Performance evaluation methodologies and standards.



For more information, please contact the Guest Editors:

Benoit Huet, EURECOM
Alexander Hauptmann, Carnegie Mellon University
Tat-Seng Chua, National University of Singapore


Submission Procedures

Submit your paper at https://mc.manuscriptcentral.com/cs-ieee. When
uploading your paper, please select the appropriate special issue title
under the category "Manuscript Type." If you have any questions regarding
the submission system, please contact Andy Morton at mm-ma@computer.org. All
submissions will undergo a blind peer review by at least two expert
reviewers to ensure a high standard of quality. Referees will consider
originality, significance, technical soundness, clarity of exposition, and
relevance to the special issue topics. All submissions must contain
original, previously unpublished research or engineering work. Papers must
stay within the following limits: 6,500 words maximum, 12 total combined
figures and tables with each figure counting as 200 words toward the total
word count, and 18 references.



To submit a paper to the July-September 2012 special issue, please observe
the following deadlines:

1 October 2011: Full paper must be submitted using our online manuscript
submission service and prepared according to the instructions for authors
(please see the Author Resources page at
15 January 2012: Authors notified of acceptance, rejection, or needed
5 April 2012: Final versions due.

Online Printable Version:

Computer Vision and Image Understanding: Special Issue on Visual
Concept Detection

Guest editors:
Bart Thomee, Yahoo! Research, Spain
Mark J. Huiskes, Leiden University, Netherlands
Michael S. Lew, Leiden University, Netherlands

Important dates:
Submission of manuscript: 1 November 2011
First notification of acceptance: 1 March 2012
Revised manuscript submission: 1 May 2012
Final notification of acceptance: 15 June 2012
Publication of special issue: Fall 2012

One of the grand challenges in multimedia information retrieval is
automatic visual concept detection. This special issue calls on
researchers that aim to raise the bar with novel approaches and
techniques. All contributions are welcomed that address the topic
of visual concept detection using the MIRFLICKR image collection,
which is a popular large-scale open test benchmark. This special
issue provides an excellent venue to publish high-quality work on
novel ideas and insights that will significantly advance the state
of the art.

The special issue centers around the MIRFLICKR image collection for
the visual concept detection challenge. This set consists of one
million images from thousands of real world users that were published
to the Flickr social photography website under a creative commons
license. To facilitate training and testing a subset of the
collection has been carefully annotated by hand. The dataset can be
obtained from http://mirflickr.liacs.nl. It is at the discretion of
the authors to use the collection in its entirety or only partially.

Besides the annotations already supplied with the dataset, the
ImageCLEF organization has additionally defined 99 concepts and 40
topics that can be expressed as a logical combination of these
concepts. Their custom MIRFLICKR collection is available to
registered participants of the ImageCLEF Photo Annotation task.
Please refer to http://www.imageclef.org/2011/Photo for more
details on this dataset. Results based on the ImageCLEF annotations
are within the scope of this special issue.

All submissions for this special issue are required to follow the
same format as regular full-length Computer Vision and Image
Understanding papers. Manuscripts must be submitted through the
CVIU online submission system at http://ees.elsevier.com/cviu.
Please ensure to select 'Special Issue: Visual Concept Detection'
as the 'Article Type'. All manuscripts should contain at least 30%
original material. When submitting a manuscript that is an expanded
version of a conference or workshop paper, this prior paper must
be included as 'Supplementary Material' during submission. All
manuscripts will be peer-reviewed according to the CVIU reviewing

If you have any questions, please contact Bart Thomee at mirflickr@yahoo.com.