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Video Surveillance Framework for Crime Prevention and Event Indexing

The paper will present a video surveillance and event detection and annotation framework for semi-supervised surveillance use. The system is intended to be used in automatic mode on camera feeds that are not actively watched by surveillance personnel, raising alarms and enrolling annotation data when unusual events occur. We present the current detector filters, and the easily extendable modular interface. Current filters include local and global unusual motion detectors, left object detector, motion detector, tampering/failure detector, etc. The system stores the events and associated data, which can be organized, searched, annotated and (re)viewed. It has been tested in real life situation for police street surveillance, and we are working towards developing a deployable version.