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ICCV - VECTaR 2011 : The 3rd International Workshop on Video Event Categorization, Tagging and Retrieval for Real-World Applications ( VECTaR2011 ) *In Conjunction with ICCV 2011

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Link: http://www.computing.dundee.ac.uk/staff/jgzhang/VECTaR2011.htm
 
When Nov 13, 2011 - Nov 13, 2011
Where Barcelona, Spain
Submission Deadline Jul 11, 2011
Notification Due Aug 22, 2011
Final Version Due Sep 12, 2011
Categories    computer vision   image processing
 

Call For Papers

------First Call for Papers------------------------

We are pleased to announce the First call for paper for The 3rd International Workshop on Video Event Categorization, Tagging and
Retrieval for Real-World Applications ( VECTaR2011 ) *In Conjunction with ICCV 2011

Details are below.

Deadline for submission: July 11th, 2011

Dates: November 13th, 2011
Location: Barcelona, Spain,
Website: http://www.computing.dundee.ac.uk/staff/jgzhang/VECTaR2011.htm

The 3rd International Workshop on Video Event Categorization, Tagging and
Retrieval for Real-World Applications ( VECTaR2011 ) *In Conjunction with ICCV
2011,

Important Dates

- Submission Deadline *July 11th, 2011*
- Notification of Acceptance *August 22nd, 2011*
- Camera-Ready Submission *September 12th, 2011*
- Workshop *November 13th, 2011*

Call for Papers

With the vast development of Internet capacity and speed, as well as wide
adoptation of media technologies in people's daily life, it is highly
demanding to efficiently process or organize video events rapidly emerged
from the Internet (e.g., YouTube), wider surveillance networks, mobile
devices, smart cameras, etc. The human visual perception system could,
without difficulty, interpret and recognize thousands of events in videos,
despite high level of video object clutters, different types of scene
context, variability of motion scales, appearance changes, occlusions and
object interactions. For a computer vision system, it has been very
challenging to achieve automatic video event understanding for decades.
Broadly speaking, those challenges include robust detection of events under
motion clutters, event interpretation under complex scenes, multi-level
semantic event inference, putting events in context and multiple cameras,
event inference from object interactions, etc.

In recent years, steady progress has been made towards better models for
video event categorization and recognition, e.g., from modeling events with
bag of spatial temporal features to discovering event context, from
detecting events using a single camera to inferring events through a
distributed camera network, and from low-level event feature extraction and
description to high-level semantic event classification and recognition.
However, the current progress in video event analysis is still far more from
its promise. It is still very difficult to retrieve or categorise a specific
video segment based on their content in a real multimedia system or in
surveillance applications. The existing techniques are usually tested on
simplified scenarios, such as the KTH dataset, and real-life applications
are much more challenging and require special attention. To advance the
progress further, we must adapt recent or existing approaches to find new
solutions for intelligent video event understanding.

The goal of this workshop is to provide a forum for recent research advances
in the area of video event categorisation, tagging and retrieval. The
workshop seeks original high-quality submissions from leading researchers
and practitioners in academia as well as industry, dealing with theories,
applications and databases of visual event recognition. Real-life
applications in the context of multimedia metadata, i.e. event analysis and
recognition on videos from the Internet, surveillance cameras, and mobile
devices, etc., will be the theme of this year鈥檚 workshop. Topics include the
following, but not limited to:

- Motion interpretation and grouping
- Human Action representation and recognition
- Abnormal event detection
- Contextual event inference
- Event recognition among a distributed camera network
- Multi-modal event recognition
- Spatial temporal features for event categorization
- Hierarchical event recognition
- Probabilistic graph models for event reasoning
- Machine learning for event recognition
- Global/local event descriptors
- Metadata construction for event recognition
- Bottom up and top down approaches for event recognition
- Event-based video segmentation and summarization
- Video event database gathering and annotation
- Efficient indexing and concepts modeling for video event retrieval
- Semantic-based video event retrieval
- On-line video event tagging
- Evaluation methodologies for event-based systems
- Event-based applications (security, sports, news, etc.)


General Chairs

- Prof. Tieniu Tan, *Chinese Academy of Sciences, China*
- Prof. Thomas S. Huang, *University of Illinois at Urbana-Champaign, USA
*

Program Chairs

- Prof. Liang Wang, *Chinese Academy of Sciences, China*
- Dr. Jianguo Zhang,* University of Dundee, UK *
- Dr. Ling Shao, *The University of Sheffield, UK*

Tentative Program Commitee

- Rama Chellappa , *University of Maryland, USA *
- James W. Davis , *Ohio State University, USA *
- Ling-Yu Duan , *Peking University, China *
- Tim Ellis , *Kingston University, UK *
- James Ferryman , *University of Reading, UK *
- GianLuca Foresti , *University of Udine, Italy *
- Shaogang Gong , *Queen Mary University London, UK *
- kaiqi Hang , *Chinese Academy of Sciences, China *
- Winston Hsu , *National Taiwan University *
- Ran He, *Chinese Academy of Sciences *
- Yu-Gang Jiang , *Columbia University, USA *
- Graeme A. Jones , *Kingston University, UK *
- Ivan Laptev , *INRIA, France *
- Jianmin Li , *Tsinghua University, China *
- Xuelong Li , *Chinese Academy of Sciences, China *
- Zhu Li , *Hong Kong Polytechnic University, China *
- Marcin Marszalek , *Unviersity of Oxford, UK *
- Tao Mei , *Microsoft Research Asia *
- Paul Miller , *Queen's University Belfast, UK *
- Ram Nevatia , *University of Southern California, USA *
- Yanwei Pang , *Tianjin University, China *
- Federico Pernici , *Universitè„¿ di Firenze, Italy *
- Carlo Regazzoni , *University of Genoa, Italy *
- Shin'ichi Satoh , *National Institute of Informatics, Japan *
- Dan Schonfeld , *University of Illinois at Chicago, USA *
- Ling Shao , *The University of Sheffield, UK *
- Yan Song , *University of Science and Technology of China *
- Peter Sturm , *INRIA, France *
- Dacheng Tao , *Sydney University of Technology, Australia *
- Xin-Jing Wang , *Microsoft Research Asia *
- Tao Xiang , *Queen Mary University London, UK *
- Dong Xu , *Nanyang Technological University, Singapore *
- Hongbin Zha , *Peking University, China *
- Zhang Zhang, *Chinese Academy of Sciences *
- Jianguo Zhang , *University of Dundee, UK *
- Lei Zhang , *Microsoft Research Asia *
- Liang Wang , *Chinese Academy of Sciences, China *
- Pingkun Yan , *Chinese Academy of Sciences, China *
- Yuan Yuan , *Chinese Academy of Sciences, China *

Submission

- When submitting manuscripts to this workshop, the authors acknowledge
that manuscripts substantially similar in content have NOT been submitted to
another conference, workshop, or journal. However, *dual submission to
the ICCV 2011 main conference and VECTaR'11 is allowed*.
- The format of a paper submission is the same as the ICCV main
conference. Please follow instructions on the ICCV 2011
websitehttp://www.iccv2011.org/paper-submission.

- For the paper submission, please go to the Submission Website (
https://cmt.research.microsoft.com/VECTAR2011/)

Review

Each submission will be reviewed by at least three reviewers from program
committee members and external reviewers for originality, significance,
clarity, soundness, relevance and technical contents. Accepted papers will
be published together with the proceedings of ICCV 2011 (included in the
main conference DVD and in IEEE Xplore). High-quality papers will be invited
to submit a special issue of a good computer vision journal after the
conference.



Contacts

- Prof. Liang Wang, wangliang@nlpr.ia.ac.cn
- Dr. Jianguo Zhang, jgzhang@computing.dundee.ac.uk
- Dr. Ling Shao,ling.shao@sheffield.ac.uk

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