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