期刊名称：ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
印刷版ISSN：2194-9042
电子版ISSN：2194-9050
出版年度：2004
卷号：XXXV Part B2
页码：134-138
出版社：Copernicus Publications
摘要：Airborne laser scanning has established itself as a dominant technology providing high quality surface data for a variety of applications. LiDAR has substantially widened the use of mapping, for instance, in the late nineties, telecommunication industry required large volumes of high-density DSM data. In addition, research has recently shown promising results in extracting features such as man-made objects, for example buildings, from the point cloud. More recently, research started to explore the feasibility of using Lidar data for transportation applications, including infrastructure, emergency and environmental mapping along corridors. Initial investigation on assessing the performance of extracting vehicles from LIDAR data and then categorizing them has proved that valuable traffic flow information can be obtained. The vehicle classification was mainly based on simple four-parameter description of the vertical profile of the vehicles. This paper is a continuation of that research effort by introducing an improved model of the vehicle profile description. A model library is formed based on the ground-based laser scanning data and an analytical approximation of the vehicle profile will replace the previous four-parameter description. The anticipated benefits are twofold: 1) a better extraction and a more robust coarse classification of the vehicles are expected, and 2) it is very likely that subclasses of vehicles can be introduced such as small cars, full-size cars, light trucks, SUVs and so on. This paper describes a newly developed model of vehicle profile description, the classification method, implementation, and algorithmic aspects. Extensive tests have been carried out to validate the method and assess its performance
关键词：LIDAR; Modeling; Automation; Data fusion; Terrestrial laser scanning
