Multi-target detection and tracking algorithm based on roadside LiDAR
In order to detect and track road targets in complex urban intersection environments,a multi-target detection and tracking algorithm based on roadside LiDAR is proposed.Firstly,the background subtraction method is used to fil-ter out the background point cloud.Then,the curved-voxel clustering algorithm is used to detect the target to obtain 3 D bounding box information with fusing 5 frame point clouds.Subsequently,a double-validation gate and life cycle man-agement strategy with adaptive threshold are put forward,which effectively improves the accuracy of object matching and reduces object missing and false detection.Finally,the fusion algorithm of Interacting Multiple Model-Unscented Kalman Filter and Joint Probability Data Association was used to track road targets.The experimental results show that the algorithm meets the real-time requirements while ensuring detection and tracking performance,and has an engi-neering application value.
LiDARmulti-target detection and trackingcurved-voxel clusteringdata associationIMM-UKF algorithm
万方数据
维普
