Socially intelligent surveillance and monitoring: Analysing social dimensions of physical space

In general terms, surveillance and monitoring technolo- gies aim at understanding what people do in a given envi- ronment, 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. However, surveillance and monitor- ing technologies rarely consider that they analyze human behavior, a phenomenon subject to principles and laws rig- orous enough to produce stable and predictable patterns corresponding to social, affective, and psychological phe- nomena. On the other hand, these phenomena are the sub- ject of other computing domains, in particular Social Signal Processing and Affective Computing, that typically neglect scenarios relevant to surveillance and monitoring technolo- gies, especially when it comes to social and affective di- mensions of space in human activities. The goal of this paper is to show that the investigation of the overlapping area between surveillance and monitoring on one side, and Social Signal Processing and Affective Computing on the other side can bring significant progress in both domains and open a number of interesting research perspectives.