文章基本信息

标题：Combining genetic algorithms with imperfect and subdivided features for the automatic registration of point clouds (GAReg-ISF)
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作者：S. Schenk ; K. Hanke
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-5/W1
出版社：Copernicus Publications
摘要：Terrestrial laser scanners have achieved a great popularity in the last decade. Their easy on-site application and the possibility of a flexible and high quality post processing added to their success also in architectural, archaeological and heritage documentation. We present a method for handling the automatic registration of point clouds which are characterized by a significant noise level, generally imperfect geometry and occlusions. Hereby we combine and extend already existing and established methods to facilitate the registration of point clouds without prior pre-processing. Our approach consists - similar to other methods - of three steps which are scan analysis, pair-wise matching and multi-view matching. To handle the above mentioned datasets we propose to use imperfect and subdivided features, and to implement Genetic Algorithms (GAs). At the same time our approach can be seen as extension to already known Genetic Algorithms used for the registration of point clouds. By implementing an adapted version of a Genetic Algorithm in the classical registration process between coarse and fine registration we are able to maintain robustness and computational performance also when registering scans of bigger objects characterised by a notably increased number of points, a significant noise level and occlusions. We show and discuss the successful application of the algorithm also on scenes which do not consist of classical geometric primitives such as planes
关键词：Terrestrial Laser Scanning; Registration; Point Clouds; Genetic Algorithms; Imperfect and Subdivided Features