Object Recognition and Tracking using Multiple LiDARs

This paper presents an object recognition and tracking method using multiple light detection and ranging sensors (LiDARs) set in an environment. Each LiDAR recognizes objects, such as cars, two-wheelers, and people, using CenterPoint, which is an end-to-end method for three-dimensional object recognition. Information about recognized objects (the position, size, heading, and the confidence score of the objects) is sent to a central server and fused using nonmaximum weighted method. The fused objects are tracked using an interacting multimodel estimator, and their poses and behavior are estimated. Simulation experiments using three LiDARs placed in an intersection environment validate the performance of the presented method.