Multi-Object Tracking with Camera-LiDAR Fusion for Autonomous Driving

arXiv:2403.04112v1 Announce Type: cross
Abstract: This paper presents a novel multi-modal Multi-Object Tracking (MOT) algorithm for self-driving cars that combines camera and LiDAR data. Camera frames are processed with a state-of-the-art 3D object detector, whereas classical clustering techniques are used to process LiDAR observations. The proposed MOT algorithm comprises a three-step association process, an Extended Kalman filter for estimating the motion of each detected dynamic obstacle, and a track management phase. The EKF motion model requires the current measured relative …

3d object abstract algorithm art arxiv association autonomous autonomous driving cars clustering cs.cv cs.ro data driving fusion lidar modal multi-modal novel object paper process self-driving state tracking type