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AISB event Bulletin Item

CFP: ECCV08 workshop Machine Learning for Vision-based Motion Analysis

Vision-based motion analysis aims to detect, track and identify objects, and more generally, to understand their behaviors, from video sequences. This exciting research area has received growing interest in recent years due to a wide spectrum of proposing applications such as visual surveillance, human-machine interface, virtual reality, and motion analysis. Statistical machine learning algorithms have been recently successfully applied to address challenging problems involved in this area. Novel statistical learning technologies have strong potential to contribute to the development of robust yet flexible vision systems. The process of improving the performance of vision systems has also brought new challenges to the field of machine learning. Solving the problems involved in object motion analysis will lead to the development of new machine learning algorithms. In return, new machine learning algorithms are able to address more realistic problems in object motion analysis and understanding.


This one-day workshop seeks to present and highlight the latest developments in vision-based object motion analysis and understanding from a machine learning perspective. It aims to bring together worldwide researchers from related disciplines, to provide a forum for the dissemination of significant research work and innovative practice, and to encourage exchanges, interactions and possible collaboration between participants.

We invite you to participate the first workshop on Machine Learning for Vision-based Motion Analysis, which will be held in conjunction with the 10th European Conference on Computer Vision (ECCV08), on Oct 17, 2008, in Marseille, France.


We solicit the high-quality, previously unpublished, research contributions that address vision-based object motion analysis by using machine learning approaches. Submissions that address real-world applications are especially encouraged. Tentative topics of interest include, but are not limited to,


 Methods: Supervised/unsupervised/semi-supervised learning; Generative and discriminative approaches; Probabilistic graphical models and exponential families; Manifold (or subspace) learning; Kernel machines; Online and incremental learning; etc


 Applications: Motion segmentation and object recognition; object detection and tracking; Motion feature extraction and representation; Pose estimation; Motion analysis and understanding; Activity analysis and unusual event detection; etc

Prospective authors are invited to submit a full-length twelve-page paper electronically via the MLVMA'08 web-page.
Important dates:
Submission deadline: July 3, 2008

Notification of acceptance: August 7, 2008

Camera-ready due: August 20, 2008

Workshop: Oct 17, 2008

Program chairs:
Matti Pietikinen,  University of Oulu, Finland
Liang Wang, The University of Melbourne, Australia
Li Cheng, National ICT Australia
Guoying Zhao, University of Oulu, Finland
Program committee:
Stefan Carlsson, Royal Institute of Technology, Sweden
Larry Davis, University of Maryland, USA
Shaogang Gong, University of London, Queen Mary, UK
Weiming Hu, Chinese Academy of Sciences, China
Fei-fei Li, Princeton University, USA
Hua Li, Chinese Academy of Sciences, China
Rainer Lienhart, Universitt Augsburg, Germany
Dimitrios Makris, Kingston University, UK
Nadia Magnenat-Thalmann, MIRALab, Switzerland

Greg Mori, Simon Fraser University, Canada

Yuichi Nakamura, Kyoto University, Japan
David Suter, Monash University, Australia
Alistair Sutherland, Dublin City University, Ireland
Cristian Sminchisescu, University of Chicago, USA
Tieniu Tan, Chinese Academy of Sciences, China
Matthew Turk, University of California, USA
Herb Yang, University of Alberta, Canada
Hongbin Zha, Peking University, China

If you have any problems, please be free to contact us:


Matti Pietikinen (

University of Oulu, Finland

Tel: +358 8 553 2782


Liang Wang (

University of Melbourne, Australia

Tel: +61 3 83441364



Li Cheng (

National ICT Australia

Tel: +61 2 6267 6322



Guoying Zhao (, Primary contact)

University of Oulu, Finland

Tel: +358 8 553 7564