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Ichiro IDE <[log in to unmask]>
Reply To:
Mon, 15 Jun 2009 20:29:32 +0900
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Dear all,

Please find below the CFP for the ACMMM2009 workshop on Multimedia for
Cooking and Eating Activities (CEA2009).
!!! The deadline has been extended due to requests. !!!

 IEEE First Workshop on Emergent Issues in Large Amounts of Visual Data
                             (WS-LAVD 2009)
                      in conjunction with ICCV2009

                    October  4, 2009 in Kyoto, Japan


             !!!!!!!! Submission deadline extended !!!!!!!!
             !!!!!!!!       to June 23, 2009       !!!!!!!!

Today, immensely large amounts of visual data are captured and recorded 
every moment. Also, we can download almost an infinite number of images 
and videos from the Internet, where the stored visual data are 
explosively increasing.

<< Can the Large Amount of Visual Aata Produce Something New? >>
   According to the idea of "quantity breeds quality", researchers are 
   trying to find out new phenomena and their applications on the large 
   amounts of visual data. "Generic object recognition", "Hallucination", 
   "Irregularity detection", and "Cascaded ADA Boosting" are the 
   successful examples. We already have these applications; however, 
   they can be extended further.

<< Arm Ourselves for Fighting with the Monster! >>
   Through these researches, we noticed that most algorithms performing 
   search, clustering, regression, and classification proposed so far 
   lose effect on a large amount of visual data. This implies that more 
   scalable algorithms and architectures have to be developed. For 
   example, compact and powerful feature descriptors, memory efficient 
   algorithms, distributed parallel architectures, and so on.

<< We Need Metallurgy for Making Strong Armor. >>
   For utilizing the visual data, label data are necessary in many cases. 
   However, labeling is always expensive and available labels are often 
   noisy. How can we make robust algorithms against such noisy labels? 
   Also, an imbalanced training set may introduce bias into classifiers. 
   How can we remove it?


	Paper submissions should be related but not limited to any of 
	the following topics: 

	<< Scalable architectures for large amounts of visual data >>
	   Cooperative Distributed Parallel systems, Multi-Agent 
	   systems, Parallel implementations of algorithms, and so on.
	<< Scalable algorithms on large amounts of visual data >>
	   Compact and powerful feature descriptors, Memory efficient 
	   scalable algorithms, External algorithms on HDD, Chunking, 
	   Serialization, and so on.
	<< Applications exploiting large amounts of visual data >>
	   Any applications using large amounts of visual data, such as 
	   Computational Photography using large amounts of images 
	   (Super-resolution, Automatic Colorization, etc), 
	   Irregularity Detection, Generic or specific object 
	   recognition, and so on.

	<< Data collection and labeling >>
	   Semi-supervised learning, Effortless labeling framework, Web 
	   crawler, and so on.

	The authors are requested to prepare their papers following the
	ICCV2009 main conference instructions. See the following URL 
	for details:

	All submitted papers are reviewed by at least two reviewers in 
	a double-blind manner. It is our policy that duplicate 
	submissions to this workshop are allowed only if the papers are
	primarily submitted to the main conference.  Papers accepted to 
	the main conference are alternatively not accepted to the 

	Paper submission deadline		June 23rd, 2009
	Paper acceptance notification		July 25th, 2009
	Camera ready submission deadline	Aug. 10th, 2009
	Workshop				Oct.  4th, 2009

	General chair		Toshikazu Wada	
				Wakayama Univ., JP

	Program chairs		Koichi Kise
				Osaka Prefecture Univ., JP

				Shin'ichi Satoh
				National Institute of Informatics, JP

	Publication chair	Takahiro Okabe
				The Univ. of Tokyo, JP

	Web chairs		Tatsuya Harada
				The Univ. of Tokyo, JP

				Keiji Yanai
				The Univ. of Electro-Communications, JP

	Publicity chair		Ichiro Ide
				Nagoya University / NII, JP

	Kobus Barnard		Univ. of Arizona, US
	Edward Chang		Google, US
	Minoru Etoh		NTT DoCoMo, JP
	Tatsuya Harada		The Univ. of Tokyo, JP
	Ichiro Ide		Nagoya University / NII, JP
	Frederic Jurie		Univ. of Caen, FR
	Koichi Kise		Osaka Prefecture Univ., JP
	Li Fei-Fei		Princeton Univ., US
	Tao Mei			Microsoft Research Asia, CN
	Chong-Wah Ngo		City Univ. of Hong Kong, HK
	Takahiro Okabe		The Univ. of Tokyo, JP
	Shin'ichi Satoh		National Institute of Informatics, JP
	Cordelia Schmid		INRIA, FR
	Josef Sivic		INRIA, FR
	Cees Snoek		Univ. of Amsterdam, NL
	Toshikazu Wada		Wakayama Univ., JP
	Haiyuan Wu		Wakayama Univ., JP
	Keiji Yanai		The Univ. of Electro-Communications, JP

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* Ichiro IDE			   [log in to unmask] / [log in to unmask] *
* Nagoya University, Graduate School of Information Science		 *
*	Phone/Facsimile: +81-52-789-3313				 *
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