This document proposes a chaos prediction system using visual surveillance and network computing. The system would use multiple surveillance cameras located in places like train stations to capture video. A prediction system would apply motion vector filtering to the video scenes to determine the center of any threats, like a bomb, based on the movement of people away from the threat. For systems with many cameras, a large amount of computation would be required, which could optionally be distributed across a network or grid computing system to handle the processing load.
PPT- Chaos Prediction using Visual Surveillance and Network Computing
1. A Novel approach for Chaos Prediction using
Visual Surveillance and Network Computing
26 - Jan - 2009
Wednesday, 4 June 14
2. Chaos Detection System Architecture
Surveillence
Camera
Prediction System
Network / Grid Computing (OPTIONAL)
Chaos
(n) Cameras located in different locations of a
particular place e.g railway station
Wednesday, 4 June 14
4. • Logic: In a public place if a threat is
detected (say bomb threat), motion of
public will be opposite to the location of
threat.
• We can predict centre of threat using
vector filtering system.
Wednesday, 4 June 14
6. • The system of a single camera demands a
large amount of computation since it
requires constant processing of scene to
compute motion of public.
• For a system with large amount of cameras
imagine what amount of computation
power is required...
Wednesday, 4 June 14
9. License Plate Recognition System
License Plate
Recognition
System
Camera Input
Feed
Vehicle
Number
Match /
Mismatch
Internet /
Network
Wednesday, 4 June 14
13. Extra
• As a pilot project this can be done using
single PC with Single Camera.
• This can be extended optionally over
model of network / grid computing.
Wednesday, 4 June 14