Abstract
Preceding vehicle detection and tracking is an important task for vision-based automatic guidance system. In this thesis, we propose a method to solve the problem which includes multi vehicle detection and multi vehicle tracking. In multi vehicle detection, we sample the image using the particle filtering theory. After sampling we are using the SVM to find the vehicle image. In multi vehicle tracking hypothesis, we find the local maximum SVM score to identify the positions of the vehicle. In the experiments, we demonstrate that our system can identify the existing preceding car as well as the passing car. Once the vehicle is detected, it will be tracked until the size of it disappear or occluded by other vehicles.