sism 2011 - 2nd IEEE Workshop on Socially Intelligent Surveillance and Monitoring

In general terms, surveillance and monitoring technologies aim at understanding what people do in a given environment, whether this means to ensure the safety of workers on the factory floor, to detect crimes occurring in indoor or outdoor settings, or to monitor the flow of large crowds through public spaces. Computer vision & pattern recognition are the main technologies used for automatic monitoring of public spaces. Effective approaches for tracking people, recognizing poses, postures, gestures, collective crowd phenomena in public environments have been developed in the last years, especially in the video surveillance context, aimed at classifying (suspect, unusual, abnormal) behaviors.

However, surveillance and monitoring technologies rarely consider that they analyze human behavior, a phenomenon subject to principles and laws rigorous enough to produce stable and predictable patterns corresponding to social, affective, and psychological phenomena. On the other hand, these phenomena are the subject of other computing domains, in particular Social Signal Processing and Affective Computing, that typically neglect scenarios relevant to surveillance and monitoring technologies, especially when it comes to social and affective dimensions of space in human activities.

The mission of SISM is to fill this gap by gathering researchers active in computer vision and pattern recognition, human sciences and automatic behavior understanding, in the same spirit as it has been pursued in the first edition of the workshop. Joint research across these communities will have a major impact on any technology that can benefit from automatic monitoring approaches, including video-surveillance, architecture, ambient intelligence, marketing, office space design, urbanism, etc..