Audio-Video Event Recognition System for Public Transport Security

This paper presents an audio-video surveillance system for the automatic surveillance in public transport vehicle. The system comprises six modules including in particular three novel ones: (i) face detection and tracking, (ii) audio event detection and (iii) audio-video scenario recognition. The face detection and tracking module is responsible for detecting and tracking faces of people in front of cameras. The audio event detection module detects abnormal audio events which are precursor for detecting scenarios which have been predefined by end-users. The audio-video scenario recognition module performs high level interpretation of the observed objects by combining audio and video events based on spatio-temporal reasoning. The performance of the system is evaluated for a series of pre-defined audio, video and audio-video events specified using an audio-video event ontology.