June 2013 Newsletter June 2013 Newsletter

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

This month's topics include:

IEEE Multimedia Magazine Special issue CFP
TCMC Executive Committee Meeting (Jul. 16th)

 
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TCMC will have a executive committee meeting on Jul. 16th,
held in conjunction with IEEE ICME'13.

http://icme2013.org/sidemeetings.php

Date: Jul. 16th
Time: Lunch (noon)
Room: Valley

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Large Scale Geo-Social Multimedia Computing

Submission deadline: August 15, 2013
Publication issue: July–September 2014

With the advance of Web 2.0 era, there is an explosive growth
of geographical multimedia shared in social network websites
such as Flickr, YouTube and Zooomr. On one hand, rather than
simply searching for and passively consuming media content,
these media repositories allow users to create and exchange
their own media data (including videos, images, music, blogs
and so on) for social interaction, which brings in a new
revolution to our social lives and underscores a transformation
of the Web as fundamental as its birth. On the other hand,
besides the plain visual signals, more and more social media
is also associated with rich location context such as GPS tags,
location name identifications and metadata, benefiting a wide
variety of potential multimedia applications such as annotation,
visual search and contextual media recommendation, multimedia
mining and so on from a more physically related point of view.
Recently, research on the location aware media description,
modeling, learning, and application in pervasive social media
analysis has become very popular. Such location context makes
the traditional difficult problems in multimedia content
analysis become more tractable. For example, large-scale
image repository can be significantly pruned if we use the
GPS information to filter out the irrelevant images with
respect to the query image. We see a timely opportunity for
organizing a special issue to bring together active researchers
to share recent progress in this exciting area. This special
issue serves as a forum for researchers all over the world to
discuss their works and recent advances in recognition and
mining of geographical aware social multimedia. Both
state-of-the-art works, as well as literature reviews, are
welcome for submission. Especially, to provide readers of the
special issue with a state-of-the-art background on the topic,
we will invite one survey paper, which will undergo peer review.



This special issue seeks to present and highlight the latest
developments on large scale multiple evidence learning for
multimedia analysis. Papers addressing interesting real-world
applications are especially encouraged. Topics of interest
include, but are not limited to,

* Location extraction, description, and modeling in social
  multimedia
* Context and content fusion in location based social multimedia
  tagging
* Location aware pervasive multimedia computing and communication
* Cross-media data mining for social media retrieval
* Mobile visual search with rich location context
* Geographical tagging and mining of social media
* Location based services and user behavior mining
* Location search and recognition oriented data collection
  and benchmarking
* Scene summarizing, landmark recognition and mining
* 3D scene modeling and virtual city navigation
* Tourism recommendation from geo-tagged multimedia on the web

Submissions should follow the guidelines set out by
IEEE MultiMedia at:

http://www.computer.org/portal/web/peerreviewmagazines/multimedia

Important Dates:

    Paper Submission: August 15, 2013
    First Notification: September 30, 2013
    Revised Manuscript: November 15, 2013
    Notification of Acceptance: December 25, 2013
    Final Manuscript Due: January 15, 2014
    Publication Date: July, 2014

Guest Editors:

 Rongrong Ji, Columbia University, USA, rrji@ee.columbia.edu
 Yi Yang, University of Queensland, Australia, yi.yang@uq.edu.au
 Nicu Sebe, University of Trento, Italy, sebe@disi.unitn.it
 Kiyoharu Aizawa, University of Tokyo, aizawa@hal.t.u-tokyo.ac.jp
 Liangliang Cao, IBM Watson Research Center, liangliang.cao@us.ibm.com