文章基本信息

标题：Model-Driven and Data-Driven Approaches Using LIDAR Data: Analysis and Comparison
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作者：F. Tarsha-Kurdi ; T. Landes ; P. Grussenmeyer 等
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：2007
卷号：XXXVI-3/W49A
页码：87-92
出版社：Copernicus Publications
摘要：Following the development of 3D data acquisition techniques like digital photogrammetry, remote sensing and airborne laser scanning, the automatic building modelling is still a challenging task. Indeed, it takes a growing place in many research fields like 3D city modelling, cartographic analysis, urban planning, visualization and Geographic Information Systems (GIS) database construction. Generally, two types of approaches characterize the automatic building reconstruction. The first one is a model-driven approach. This parametric modelling approach consists of searching the most appropriate model among basic building models contained in a models library. The second one is a data-driven approach, also called non-parametric modelling approach. This technique attempts to model a primitive or a complex building by using series of more or less complex operations. It allows the generation of a model without belonging to a specific library. After an extensive state of the art, this paper confronts methods belonging to each type of automatic building construction approach. Based on a concrete experiment, the essential points characterizing each approach, including their concept and the obtained model characteristics are analysed. It is of great interest to study these issues, since not many of such investigations have been made before and have delivered the useful formulas. Consequently, improvements are introduced and have led to develop a new method for each approach. After comparison of the accuracy of these two methods and the characteristics of the resulting models, some solutions and recommendations are proposed
关键词：LIDAR; Detection; Three-dimensional; Building; Modelling; Automation; Reconstruction; Accuracy