Extraction of Vehicle Groups in Airborne Lidar Point Clouds with Two-Level Point Processes

Börcs, Attila and Benedek, Csaba (2015) Extraction of Vehicle Groups in Airborne Lidar Point Clouds with Two-Level Point Processes. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 53 (3). pp. 1475-1489. ISSN 0196-2892


Download (5MB) | Preview


In this paper we present a new object based hierarchical model for joint probabilistic extraction of vehicles and groups of corresponding vehicles - called traffic segments - in airborne Lidar point clouds collected from dense urban areas. Firstly, the 3-D point set is classified into terrain, vehicle, roof, vegetation and clutter classes. Then the points with the corresponding class labels and echo strength (i.e. intensity) values are projected to the ground. In the obtained 2-D class and intensity maps we approximate the top view projections of vehicles by rectangles. Since our tasks are simultaneously the extraction of the rectangle population which describes the position, size and orientation of the vehicles and grouping the vehicles into the traffic segments, we propose a hierarchical, Two-Level Marked Point Process (L2MPP) model for the problem. The output vehicle and traffic segment configurations are extracted by an iterative stochastic optimization algorithm. We have tested the proposed method with real data of a discrete return Lidar sensor providing up to four range measurements for each laser pulse. Using manually annotated Ground Truth information on a data set containing 1009 vehicles, we provide quantitative evaluation results showing that the L2MPP model surpasses two earlier grid-based approaches, a 3-D point-cloud-based process and a single layer MPP solution. The accuracy of the proposed method measured in F-rate is 97% at object level, 83% at pixel level and 95% at group level.

Item Type: Article
Subjects: Q Science > QA Mathematics and Computer Science > QA75 Electronic computers. Computer science / számítástechnika, számítógéptudomány
Divisions: Distributed Events Analysis Research Laboratory
Depositing User: Csaba Benedek
Date Deposited: 10 Jul 2014 12:09
Last Modified: 22 Sep 2014 08:18
URI: https://eprints.sztaki.hu/id/eprint/7835

Update Item Update Item