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ECCV 2016 : Workshop on Crowd Understanding ECCV 16: Call for papers


When Oct 8, 2016 - Oct 9, 2016
Where Amsterdam
Submission Deadline Jun 1, 2016
Notification Due Jul 4, 2016
Final Version Due Jul 25, 2016
Categories    computer vision   people tracking   crowd understanding

Call For Papers

The International Workshop on Crowd Understanding aims to bring together people from academic/scientific and industrial/business communities active in computer vision and video surveillance fields in order to initiate a discussion regarding the state of the art, outlooks and challenges in the field with an accent on the business aspects of the technologies.

Fast increasing hardware capabilities, growing data bandwidth and falling costs cause surveillance cameras to be deployed in large quantities, inducing a strong need for automated processing with an ultimate goal of scene understanding. Despite the significant effort of the Computer Vision scientific community, the state of the art video surveillance automation is based on tracking individual persons in sparsely crowded environments while automated understanding of crowded scenes remains an unsolved problem. Being an unsolved problem in scientific research, it also represents a missing piece in commercial automated video surveillance systems. There it also represents a high potential for commercialization – the large amount of surveillance cameras causes either cognitive overload of security operators or increased operating costs creating a strong and urgent need for automation.

We invite the submission of high quality manuscripts describing unpublished work from researchers and practitioners who are active in the following areas:

Novel Crowd Understanding Techniques
Detection and tracking of crowd
Recognition and detection of crowd behavior
Single camera people detection and tracking in crowded environments
Multi camera people detection and tracking in crowded environments
Abnormality detection in crowd
People re-identification in crowded scenes
Crowd analytics, such as density estimation
F-formation recognition
Novel sensors and surveillance system architecture for crowd understanding
Crowd datasets
Business and societal aspects of crowd surveillance
Other computer vision topics related to crowd monitoring

Papers describing novel solutions which have real potential for business exploitation are particularly encouraged.


François Brémond, INRIA Sophia Antipolis.
Vít Líbal, Honeywell ACS Global Labs Prague
Andrea Cavallaro, Queen Mary University of London.
Tomas Pajdla, Czech Technical University in Prague.
Petr Palatka, Neovision s.r.o.

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