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Traffic sign detection in MLS acquired point clouds for geometric and image-based semantic inventory

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Show simple item record Soilán Rodríguez, Mario Riveiro Rodríguez, Belén Martínez Sánchez, Joaquín Arias Sánchez, Pedro 2019-10-09T08:57:44Z 2019-10-09T08:57:44Z 2016-04
dc.identifier.citation ISPRS Journal of Photogrammetry and Remote Sensing, 114, 92-101 (2016) spa
dc.identifier.issn 09242716
dc.description.abstract Nowadays, mobile laser scanning has become a valid technology for infrastructure inspection. This technology permits collecting accurate 3D point clouds of urban and road environments and the geometric and semantic analysis of data became an active research topic in the last years. This paper focuses on the detection of vertical traffic signs in 3D point clouds acquired by a LYNX Mobile Mapper system, comprised of laser scanning and RGB cameras. Each traffic sign is automatically detected in the LiDAR point cloud, and its main geometric parameters can be automatically extracted, therefore aiding the inventory process. Furthermore, the 3D position of traffic signs are reprojected on the 2D images, which are spatially and temporally synced with the point cloud. Image analysis allows for recognizing the traffic sign semantics using machine learning approaches. The presented method was tested in road and urban scenarios in Galicia (Spain). The recall results for traffic sign detection are close to 98%, and existing false positives can be easily filtered after point cloud projection. Finally, the lack of a large, publicly available Spanish traffic sign database is pointed out. spa
dc.description.sponsorship Spanish Ministry of Economy and Competitiveness | Ref. TIN201346801-C4-4-R spa
dc.description.sponsorship Xunta de Galicia | Ref. CN2012/269 spa
dc.description.sponsorship Dirección General de Tráfico | Ref. SPIP20151500 spa
dc.description.sponsorship FPI | Ref. BES-2014-067736 spa
dc.language.iso eng spa
dc.publisher ISPRS Journal of Photogrammetry and Remote Sensing spa
dc.title Traffic sign detection in MLS acquired point clouds for geometric and image-based semantic inventory spa
dc.type article spa
dc.rights.accessRights openAccess spa
dc.identifier.doi 10.1016/j.isprsjprs.2016.01.019
dc.identifier.editor spa
dc.publisher.departamento Enxeñaría dos materiais, mecánica aplicada e construción spa
dc.publisher.departamento Enxeñaría dos recursos naturais e medio ambiente spa
dc.publisher.grupoinvestigacion Xeotecnoloxías Aplicadas spa
dc.subject.unesco 3305.06 Ingeniería Civil spa 2019-10-08T08:06:15Z

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