A particle filtering approach for joint vehicular detection and tracking in lidar data

This paper presents a method for joint detection and tracking of vehicles in scanning laser range data. Many methods use a solution that processes the raw data in a detection procedure and then tracks the detected object in an association/tracking procedure. The proposed approach uses a preclustering stage (SIP) as an input of the tracking process that allows to manage the displacement of the center-of-gravity and the changes in the apparent shape from object and motion modeling. The global problem is then described using a state-space modeling which is solved by a nonlinear filtering method.