1. Vision Surveillance
Paul Scovanner

2. Surveillance Main tasks Locating people and objects in a scene
Background Subtraction
Object Detection
Track objects as they move
Associate objects across frames
Beyond Tracking

3. Background Subtraction
Remove the background leaving areas where movement occurs
Frame Differencing:
|framet – framet-1| > Threshold

4. Background Subtraction
Frame Differencing
Fast
Simple
Error prone
(Illumination changes, Edges on large objects, Amplifies sensor noise)
Background Modeling
|framet – Background| > Threshold
Model the colors of each pixel as a Gaussian
(mean and standard deviation)
Still cant detect stationary objects

5. Background Subtraction
Mixture of Gaussians

6. Object Detection aka “is that a car or a person?”
Aspect ratio
Object Detectors

7. Tracking We can detect moving objects
(If background subtraction works)
We can identify pedestrians and cars
(If object detection works)
What’s left?

8. Tracking Associate the detections in one frame with the next.
Visual similarity
Spatial location

9. Tracking

10. Multi-view Tracking
If 1 camera is good…
3 Must be better

11. Multi-view Tracking

12. Multi-view Tracking

13. Tracking From The Air

14. Tracking From The Air

15. Tracking From The Air

16. Tracking Prediction Pedestrian Modeling
Predict movements of pedestrians

17. Anomaly Detection
Detect emergency events

18. Anomaly Detection

19. More Than Just Tracking
Crowd instability