Title :
LiDAR based vehicle detection in urban environment
Author :
Feihu Zhang ; Clarke, Daniel ; Knoll, Aaron
Author_Institution :
Robot. & Embedded Syst., Tech. Univ. Munchen, München, Germany
Abstract :
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.
Keywords :
object detection; optical radar; radar imaging; traffic engineering computing; LiDAR; hypothesis generation phase; hypothesis verification phase; light intensity; range information; urban environment; vehicle detection; Cameras; Laser radar; Shape; Support vector machines; Three-dimensional displays; Vehicle detection; Vehicles;
Conference_Titel :
Multisensor Fusion and Information Integration for Intelligent Systems (MFI), 2014 International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4799-6731-5
DOI :
10.1109/MFI.2014.6997723