Vision Surveillance Paul Scovanner

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

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

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

Background Subtraction Mixture of Gaussians

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

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

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

Tracking

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

Multi-view Tracking

Multi-view Tracking

Tracking From The Air

Tracking From The Air

Tracking From The Air

Tracking Prediction Pedestrian Modeling Predict movements of pedestrians

Anomaly Detection Detect emergency events

Anomaly Detection

More Than Just Tracking Crowd instability