Section: New Results

Unsupervised Sudden Group Movement Discovery for Video Surveillance

Participants : Sofia Zaidenberg, Piotr Bilinski, François Brémond.

keywords: Sudden Group Movement Discovery, Video Surveillance.

In this work we address the problem of discovering “sudden” movements in video surveillance videos. We propose an unsupervised approach which automatically detects quick motions in a video, corresponding to any action. A set of possible actions is not required and the proposed method successfully detects potentially alarm-raising actions without training or camera calibration. Moreover the system uses a group detection and event recognition framework to relate detected sudden movements and groups of people, and provides a semantic interpretation of the scene. We have tested our approach on a dataset of nearly eight hours of videos recorded from two cameras in the Parisian subway for a European Project. For evaluation we annotated one hour of sequences containing 50 sudden movements. Our system, if parametrized to a high sensitivity, detects $100\%$ of what the annotator considered as sudden potentially dangerous events, with a false positive rate of $21.2\%$. Setting the sensitivity to lower values we decrease the false positive rate to only $5.3\%$ but we also decrease the success rate to $76\%$. An example of an unusual sudden movement annotated by a human and detected by our approach is presented in Figure 32 . This work has been published in [49] .

Figure 32. Example of an unusual sudden movement detected by our approach.