[image 00980] First IEEE International Conference on Multimedia Big Data

[Kiyoharu Aizawa]

IEEE Multimedia Big Dataの締め切りが19日まで延びました。
ぜひご投稿を！

相澤
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Due to many requests, the submission deadline has been
extended to Dec. 19, 2014 (11:59pm PST).
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We apologize if you receive multiple copies.
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Call for Papers
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First IEEE International Conference on Multimedia Big Data
IEEE BigMM2015
April 20-22, 2015, Beijing, China
http://www.BigMM.org 

Sponsored by IEEE Computer Society

Multimedia is increasingly becoming the "biggest big data" as the most important and valuable 
source for insights and information. It covers from everyone's experiences to everything 
happening in the world. As such, multimedia big data is spurring on tremendous amount of 
research and development of related technologies and applications. 

The IEEE International Conference on Multimedia Big Data (BigMM), jointly sponsored by the 
IEEE-TCMC (Technical Committee on Multimedia Computing) and IEEE-TCSEM (Technical Committee 
on Semantic Computing), is a world's premier forum of leading scholars in the highly active 
multimedia big data research, development and applications. The first BigMM conference, with 
the theme "Multimedia: The Biggest Big Data", will be held in Beijing, China, from 
April 20 to 22, 2015, hosted by Peking University.

Please refer to the conference website for further information: 
http://www.BigMM.org/

The conference solicits high-quality original research papers in any aspect of multimedia 
big data. Topics include, but are not limited to:

- New theory and models for multimedia big data computing
- Ultra-high efficiency compression, coding and transmission for multimedia big data
- Content analysis and mining for multimedia big data
- Semantic retrieval of multimedia big data
- Deep learning and cloud computing for multimedia big data
- Green computing for multimedia big data (e.g., high efficiency storage)
- Security and privacy in multimedia big data
- Interaction, access, visualization of multimedia big data
- Multimedia big data systems
- Novel and incentive applications of multimedia big data in various fields (e.g., search, 
  healthcare, transportation, and retail)

SUBMISSIONS
Regular Papers and Industry Papers. 
Authors are invited to submit a regular paper (two-column 8 pages maximum) or an industry paper 
(two-column 6 pages maximum) according to the guidelines available on the BigMM 2015 website.

Demonstration Papers. 
Authors are invited to submit a demonstration paper (two-column 2 pages maximum) according to 
the guidelines available on the BigMM 2015 website.

BigMM Challenge. 
Each year, the organizing committee will organize an algorithmic competition to address one grand 
challenge in the field of multimedia big data which is open to all tool vendors, academics and 
corporations. The topic of the BigMM 2015 Challenge is large-scale object tracking over a network 
of multiple cameras. More information is available on the BigMM 2015 website.

Workshops Proposals. 
The organizing committee invites proposals for workshops to be held in conjunction with the conference. 
These will focus on specific topics of the main conference. More information is available on the BigMM 
2015 website.

All papers in this conference will be included in the IEEExplore and indexed by EI. Authors of high 
quality papers will be invited to submit an extended version to the special issues on 
"Multimedia: The Biggest Big Data" of the IEEE Transactions on Multimedia.


IMPORTANT DATES

Regular Paper Submission: 11:59pm PST, Dec. 19, 2014 (extended)
Demo Paper & Poster Paper Submission: 11:59pm PST, Dec. 19, 2014 (extended)
Industry Paper Submission: 11:59pm PST, Dec. 19, 2014 (extended)
Workshop Proposals: 11:59pm PST, Nov. 28, 2014
Notification of paper acceptance: Jan. 31, 2015
Camera-ready of accepted papers: Feb. 14, 2015
BigMM Challenge: Sept. 2014 - Jan. 2015
Conference: Apr. 20-22, 2015

-- 
Kiyoharu Aizawa, Professor
University of Tokyo
Dept. of Information and Communication Eng.
tel: +81-3-5841-6651
email: aizawa ＠ hal.t.u-tokyo.ac.jp