Authors:
Sofia Zaidenberg
;
Piotr Bilinski
and
François Brémond
Affiliation:
Inria, France
Keyword(s):
Event Detection, Motion Estimation, Anomaly Estimation, Situation Awareness, Scene Understanding, Group Activity Recognition, Stream Selection.
Related
Ontology
Subjects/Areas/Topics:
Applications and Services
;
Camera Networks and Vision
;
Computer Vision, Visualization and Computer Graphics
;
Motion, Tracking and Stereo Vision
;
Video Surveillance and Event Detection
Abstract:
This paper presents a novel and unsupervised approach for discovering “sudden” movements in video 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 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.