Trends in Computer Vision Automatic Video Surveillance.

Overview Why do we need automatic surveillance for Criminal and Anti-social behaviour detection? Research Issues and some solutions Commercial Solutions? Ethical and Moral Issues Conclusions and Future Developments

Why do we need Automatic Surveillance? A surveillance control room operator monitors up to 50 cameras simultaneously. More and more cameras are being placed in public areas. Recognition/prediction of violent/antisocial or criminal acts.

Researched Solutions Potential anti-social and criminal behaviour between people can be predicted by humans. –There are key types of body motion that allow predictions to be made. –Will They Have A Fight? The Predictability of Natural Behaviour Viewed Through CCTV Cameras, Troscianko et al. European Conference on Visual Perception 2001

Researched Issues and Some Solutions Building blocks for automatic surveillance. Video Scene Extract features Track people/vehicles Action/Gesture Recognition Learn Topology of Scene Detect Unusual Behaviour

Researched Issues and Some Solutions Feature Extraction –sdfsdfs Video Scene Extract features Track people/vehicles Action/Gesture Recognition Learn Topology of Scene Detect Unusual Behaviour

Researched Issues and Some Solutions Learning Scene Topology –Occlusion Analysis: Learning and Utilising Depth Maps in Object Tracking Greenhill et al, British Machine Vision Conference 2004 –Learning Spatial Context from tracking using Penalised Likelihoods, McKenna and Nait-Charif, International Conference on Pattern Recognition 2004 Video Scene Extract features Track people/vehicles Action/Gesture Recognition Learn Topology of Scene Detect Unusual Behaviour

Researched Issues and Some Solutions Tracking people/vehicles –Tracking Multiple Humans in Crowded Environment, Zhao and Nevatia, Conference on Computer Vision and Pattern Recognition 2004 –Rapid Object Detection using a Boosted Cascade of Simple Features, Viola and Jones, Conference on Computer Vision and Pattern Recognition 2001 Video Scene Extract features Track people/vehicles Action/Gesture Recognition Learn Topology of Scene Detect Unusual Behaviour

Researched Issues and Some Solutions Unusual Activity Detection –Detecting Unusual Activity in Video, Zhong et al, Conference on Computer Vision and Pattern Recognition 2004 Video Scene Extract features Track people/vehicles Action/Gesture Recognition Learn Topology of Scene Detect Unusual Behaviour

Researched Issues and Some Solutions Action/Gesture Recognition Video Scene Extract features Track people/vehicles Action/Gesture Recognition Learn Topology of Scene Detect Unusual Behaviour

Commercial Solutions Most software is based around motion sensors. Very few deal with real-time intelligent video processing. OpenCV –provides some open source tools for making your own commercial systems ( for a fee!). E.g face detection

Commercial Solutions Safehouse Technology Ltd –demo on face detection –demo on appartment block

Ethical and Moral Issues Advantages: –Potential for quicker response times. –Frees up law enforcement resources to chase other more complex crimes. Disadvantages: –Big Brother We are being captured by more and more security cameras. –Face Recognition Concerns about people having access to large databases of faces.

Conclusions and Future Developments There is still a long way to go… Integrated camera systems for cross-camera criminal event detection.