Title | Automatic road object extraction from Mobile Mapping Systems |
Publication Type | Conference Paper |
Year of Publication | 2012 |
Authors | Mancini A, Frontoni E, Zingaretti P |
Conference Name | Proceedings of 2012 8th IEEE/ASME International Conference on Mechatronic and Embedded Systems and Applications, MESA 2012 |
Abstract | Mobile Mapping Systems (MMSs) often represent the best choice to provide an accurate 3D modeling of the environment, especially in urban streets where the aerial/satellite surveys do not provide accurate data. MMSs are equipped with many kinds of sensors, and, in particular, laser scanners that allow 2D/3D environment modeling from very dense point clouds. Usually an operator manually explores the point cloud to discover and mark a particular feature of interest (e.g., road line, cross-walk). Obviously this procedure is tedious and expensive. One of the greater challenges is to automatically extract objects/features from co-registered data coming from LiDAR, optical and positioning sensors. This paper presents an automatic feature/object approach to extract and then to georeference with high accuracy/precision horizontal road signs, mainly lanes and crosswalks. The proposed approach exploits image processing techniques and methods for the 3D to 2D re-projection of data. The results obtained demonstrate that is possible to achieve accuracy and precision in the range of one centimeter. © 2012 IEEE. |
URL | http://www.scopus.com/inward/record.url?eid=2-s2.0-84867444429&partnerID=40&md5=bbdfcd587f93e0fdf60be30447684e89 |
DOI | 10.1109/MESA.2012.6275575 |
Automatic road object extraction from Mobile Mapping Systems
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