LiDAR based vehicle detection in urban environment
Feihu Zhang, Daniel Clarke, Alois Knoll · 2014
In this paper, a LiDAR based vehicle detection approach is proposed with the goal of utilizing range information. The proposed approach is based on two phases: a hypothesis generation phase to generate the potential regions and a hypothesis verification phase to recognize the corresponding vehicles. In contrast to appearance based vehicle detection systems, the proposed approach solely relies on the range information and achieves a close performance to the state-of-art. Furthermore, the proposed approach is adaptable to the environment constrains in contrast to vision based techniques, e.g. light intensity and fields of view. Performance of the proposed approach is evaluated on a large public dataset in urban environment.