A tracking with appearance modelling system for pedestrians is described. For pedestrian detection a cascade of boosted classiers and Haar-like rectangular features are used. Statistical modelling in the HSV colour space is used for adaptive background modelling and subtraction, where the use of circular statistics for hue is proposed. A clipping algorithm based on this background model and extensions to the traditional boosted classifier for fast classification are introduced. By using the background model in combination with the detector, the system extracts a feature vector based on colour statistics and spatial information. Circular and linear statistics are applied on the extracted features to robustly track the pedestrians and other moving objects. An adaptive appearance model copes with partial or full occlusions and addresses the problem of missing or wrong detections in single frames.
11th Computer Vision Winter Workshop (CVWW), Telc, Czech Republik, 6-8.2.2006, ISBN: 80-239-6530-1, Pages 105 - 110, 2006.