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June 11, 2015, Boston, MA, United States in association with CVPR 2015
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The following papers have been accepted: 3,5,6,7,8,10,14,17,21.
Congratulations!
The received reviews are now visible in the CMT website: https://cmt.research.microsoft.com/GROW2015
Please note that the time schedule for final paper submission is very tight: the deadline for submitting the camera ready version is April 27th, 2015 (next Monday!).

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Group And Crowd Behavior Analysis And Understanding

Description

After years of research on the analysis of individuals by automatic methods, the computer vision community has transferred its attention on the new issue of modeling gatherings of people, commonly referred as groups or crowds, depending on the number of people involved.

The aim of GROW 2015 is to bring together a wide range of researchers in computer vision and machine learning from one side, and applied social sciences on the other, to share innovative ideas and solutions for exploiting the potential synergies emerging from the integration of the two domains, for a range of different applications. For this reason, the invited speakers of the workshop will come from the computer science and from the social science domains, promoting an intriguing cross-fertilization among the two areas. This will serve to get an answer to many unresolved issues in the computer vision community, like: what is a group and what is a crowd? Is it true that the difference among them is a matter of number of people involved? Are there cues other than the spatial proximity and oriented velocity which could be used to detect them? Are there different typologies of groups and crowds? For example, in the sociological literature, social studies defined different kinds of crowd (spectator crowd, casual crowd, protest crowds and some other) and it could be interesting to understand whether these definitions could have some computational counterpart. Are there issues for sociologists which could be faced using computational methods (like annotations, massive observations by ecological camera networks)? The aim of the workshop will be that of explicitly managing these issues, having also a panel discussion at the end of the event.

SCOPE

To address these challenges, contributions are particularly welcome in the following areas:
  • Group/crowd detection
  • Group/crowd tracking
  • Tracking in the crowd
  • Group/crowd modeling from a drone
  • Egovision for group/crowd modeling
  • Group/crowd behavior understanding and activity recognition
  • Crowd counting
  • Group profiling
  • Information fusion for crowd modeling
  • F-formation/free conversational groups recognition
  • Jointly focused/commonly focused gathering recognition
  • Causal, spectator, protest crowd recognition and modeling
  • Abnormality detection in a group/crowd
  • Group detection in a crowd
  • Crowd forecasting
  • Metrics for group and crowd modeling
  • Video surveillance and sensor networks
  • (Collective) Head orientation, gesture recognition in groups and crowd
  • Groups and crowds datasets
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