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：2009
卷号：XXXVIII-3/W4
页码：35-40
出版社：Copernicus Publications
摘要：This paper presents a generic scheme to analyze urban traffic via vehicle motion indication from airborne laser scanning (ALS) data.The scheme comprises two main steps performed progressively － vehicle extraction and motion status classification. The step forvehicle extraction is intended to detect and delineate single vehicle instances as accurate and complete as possible, while the step formotion status classification takes advantage of shape artefacts defined for moving vehicle model, to classify the extracted vehiclepoint sets based on parameterized boundary features, which are sufficiently good to describe the vehicle shape. To accomplish thetasks, a hybrid strategy integrating context-guided method with 3-d segmentation based approach is applied for vehicle extraction.Then, a binary classification method using Lie group based distance is adopted to determine the vehicle motion status. However, thevehicle velocity cannot be derived at this stage due to unknown true size of vehicle. We illustrate the vehicle motion indicationscheme by two examples of real data and summarize the performance by accessing the results with respect to reference datamanually acquired, through which the feasibility and high potential of airborne LiDAR for urban traffic analysis are verified
