Section: New Results

Towards Unsupervised Sudden Group Movement Discovery for Video Surveillance

Participants : Sofia Zaidenberg, Piotr Bilinski, François Brémond.

keywords: Event detection; Motion estimation; Anomaly estimation; Situation awareness; Scene Understanding; Group Activity Recognition; Stream Selection

We present a novel and unsupervised approach for discovering “sudden” movements in surveillance videos. The proposed approach 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 to provide a semantical interpretation of the scene. We have tested our approach on a dataset of nearly 8 hours of videos recorded from two cameras in the Parisian subway for a European Project. For evaluation, we annotated 1 hour of sequences containing 50 sudden movements.

This work has been published in [47] .