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：2008
卷号：XXXVII Part B3b
页码：593-598
出版社：Copernicus Publications
摘要：Automatic acquisition and analysis of traffic-related data has already a long tradition in the remote sensing community. Similarly airborne laser scanning (ALS) has emerged as an efficient means to acquire the detailed 3D large-scale DSMs. The aim of this work is to initialize research work on using ALS to extract the traffic-flow information focusing on urban areas. The laser data acquisition configuration has firstly to be analyzed in order to obtain the optimal performance with respect to the reconstruction of traffic- related objects. Mutual relationships between various ALS parameters and vehicle modeling in the laser points are to be elaborated. Like other common tasks in object recognition, vehicle models for detection and motion indication from the laser data are presented; moreover, an ALS simulator is implemented to clarify and validate motion artifact in laser data. Finally, a concept for recognizing vehicles are proposed based on a vehicle and context model, which establishes a direct working flow simulating the human inference routine
