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2009
ACM

Next generation map making: geo-referenced ground-level LIDAR point clouds for automatic retro-reflective road feature extractio

9 years 5 months ago
Next generation map making: geo-referenced ground-level LIDAR point clouds for automatic retro-reflective road feature extractio
This paper presents a novel method to process large scale, ground level Light Detection and Ranging (LIDAR) data to automatically detect geo-referenced navigation attributes (traffic signs and lane markings) corresponding to a collection travel path. A mobile data collection device is introduced. Both the intensity of the LIDAR light return and 3-D information of the point clouds are used to find retroreflective, painted objects. Panoramic and high definition images are registered with 3-D point clouds so that the content of the sign and color information can subsequently be extracted. Categories and Subject Descriptors I.4 [Artificial Intelligence]: Image Processing and Computer Vision General Terms algorithm Keywords LIDAR, geo-reference, retro-reflective, lane marking, sign, road, ground-level
Xin Chen, Brad Kohlmeyer, Matei Stroila, Narayanan
Added 16 Aug 2010
Updated 16 Aug 2010
Type Conference
Year 2009
Where GIS
Authors Xin Chen, Brad Kohlmeyer, Matei Stroila, Narayanan Alwar, Ruisheng Wang, Jeff Bach
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