Vehicle detection and tracking by collaborative fusion between laser scanner and camera

This paper presents a new approach to fuse 3D and 2D information in a driver assistance setup, in particular to perform obstacle detection and tracking. We propose a new cooperative fusion method between two exteroceptive sensors: it is able to address highly non linear dynamic configuration without any assumption on the driving maneuver. Information are provided by a mono-layer laser scanner and a monocular camera which are unsynchronized. The initial detection stage is performed using the 1D laser data, which computes clusters of points which might correspond to vehicles present on the road. These clusters are projected to the image to define targets, which will be tracked using image registration techniques. This multi-object association and tracking scheme is implemented using belief theory integrating temporal and spatial information, which allows the estimation of the dynamic state of the tracks and to monitor appearance and disappearance of obstacles. Accuracy of the method is evaluated on a database made publicly available, focus is cast on the relative localization of the vehicle ahead: estimations of its longitudinal and lateral distances are analysed.