A Filter for Visual Tracking Based on a Stochastic Model for Driver Behaviour


A Filter for Visual Tracking Based on a Stochastic Model for Driver Behaviour

S.J. Maybank, A.D. Worrall, G.D. Sullivan

Department of Computer Science

The University of Reading

Abstract

A driver controls a car by turning the steering wheel or by pressing on the accelerator or the brake. These actions are modelled by Gaussian processes, leading to a stochastic model for the motion of the car. The stochastic model is the basis of a new filter for tracking and predicting the motion of the car, using measurements obtained by fitting a rigid 3D model to a monocular sequence of video images. Experiments show that the filter easily outperforms traditional filters.

Postscript (56Kb)


Last Modified: 05:14pm BST, July 14, 1997