Moving Object Detection and Tracking with Doppler LiDAR

Abstract

In this paper, we present a model-free detection-based tracking approach for detecting and tracking moving objects in street scenes from point clouds obtained via a Doppler LiDAR that can not only collect spatial information (e.g., point clouds) but also Doppler images by using Doppler-shifted frequencies. Using our approach, Doppler images are used to detect moving points and determine the number of moving objects followed by complete segmentations via a region growing technique. The tracking approach is based on Multiple Hypothesis Tracking (MHT) with two extensions. One is that a point cloud descriptor, Oriented Ensemble of Shape Function (OESF), is proposed to evaluate the structure similarity when doing object-to-track association. Another is to use Doppler images to improve the estimation of dynamic state of moving objects. The quantitative evaluation of detection and tracking results on different datasets shows the advantages of Doppler LiDAR and the effectiveness of our approach.