Pedestrian Tracking Based on Colour and Spatial Information

Florian H. Seitner, Brian C. Lovell

Abstract: This paper describes a tracking with appearance modelling system for pedestrians. A cascade of boosted classifiers and Haar-like rectangular features [6, 12] are used for the pedestrian detection. 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. By using the background model in combination with the detector, the system extracts a feature vector based on colour statistics and the spatial information. Circular [9] and linear statistics are applied on the extracted features to robustly track the pedestrians and other moving objects through the scene. An adaptive appearance model copes with partial or full occlusions and addresses the problem of missing or wrong detections in single frames.