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>>> Workshop on <<<
>>> Multimodal Pervasive Video Analysis <<<
>>> (MPVA 2010) <<<
>>> Oct. 29, 2010 - Florence, Italy <<<
>>> held in conjuction with ACM Multimedia 2010 <<<
>>> http://profs.sci.univr.it/~cristanm/MPVA2010/ <<<
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--- Rationale

Thanks to the confluence of urban monitoring applications and portable
cameras carried by humans everywhere, video acquisition, processing, and
storage systems have become an integral part of the fabric of today’s life.

Besides the classical applications such as security and surveillance, cameras
have been considered for creating novel applications based on the notions of
smart homes, ambient intelligence, human-computer interaction, social networks,
ambient assisted living, smart seminar rooms, building emergency management,
assistive technologies, and many more.

Cameras are mounted at fixed location in the urban infrastructure, or are moved
around by humans or vehicles. Fusion of data between the cameras is explored as a
means to enhance the interpretation task or to add confidence to the monitoring
results. Such fusion can occur across different spatio-temporal levels and between
subsets of fixed and mobile cameras as per the needs of the application and the
availability of valuable information from each camera.

This workshop aims to act as a forum for sharing new techniques and applications
based on pervasive video analysis for researchers, developers and practitioners
from academia and industry.

Addressing new challenges related to processing of distributed observations with
a network of cameras and applications based on joint video analysis between fixed
and mobile cameras will be the subjects of interest. Techniques and applications
based on fixed or mobile camera systems will also be considered.

--- Important deadlines

June 10, 2010: Submission of full papers
July 10, 2010: Notification of acceptance
July 15, 2010: Camera-ready full paper


--- Topics

Considering the use of multiple video streams from fixed, mobile and mixed camera networks,
topics of interest include (but are not limited to):

- Spatial and temporal reasoning
- Sensory integration and data fusion
- Situation awareness and understanding
- Multi-camera networks, including the use of IR/NIR, thermal, stereo, and 3D cameras
- Multi-camera detection and tracking
- Short/long-term re-identification (of individuals, groups)
- Short/long-term multi-camera action/activity/behavior recognition
- Short/long-term individual/group interaction analysis
- Crowd/group flow and behavior analysis
- Gesture recognition
- Behavior models
- Spatial or temporal relationships of objects and events
- Interaction of user with objects, environments
- User’s activity, location, expression, or emotional state
- Human interaction
- Event interpretation and detection of abnormal behaviors
- Active vision
- Guided vision based on high-level reasoning
- Human behavior modeling based on observations
- Applications in smart environments, ambient intelligence, domotics, surveillance and monitoring


--- Organizing committee

- Hamid Aghajan, Stanford University, USA
- Marco Cristani, University of Verona/Istituto Italiano di Tecnologia, Italy
- Vittorio Murino, Istituto Italiano di Tecnologia/University of Verona, Italy
- Nicu Sebe, University of Trento, Italy


--- Program committee

- Anup Basu (University of Alberta)
- Jian Cheng (Chinese Academy of Sciences)
- Isaac Cohen (Honeywell)
- Rita Cucchhiara (Univeristy of Modena and Reggio Emilia)
- Daniel Gatica-Perez (IDIAP)
- Shaogang Gong (Queen Mary University of London)
- Yuri Ivanov (MERL)
- Richard Kleihorst (Vito and Univ. of Gent)
- Rainer Lienhart (University of Augsburg)
- Philippos Mordohai (Stevens Institute of Technology)
- Louis-Philippe Morency (Institute for Creative Technologies)
- Fabio Pianesi (Fondazione Bruno Kessler)
- Massimo Piccardi (University of Technology, Sydney)
- Albert Ali Salah (Informatics Institute, University of Amsterdam)
- Thomas Sikora (Technische Universität Berlin )
- Rainer Stiefelhagen (University of Karlsruhe)
- Tony Xiang (Queen Mary University of London)
- Jie Yang (School of Computer Science, Carnegie Mellon)