Joint 2-D-3-D Traffic Sign Landmark Data Set for Geo-Localization Using Mobile Laser Scanning Data

This paper presents a framework to build a joint 2-D-3-D traffic sign landmark data set for geo-localization using mobile laser scanning (MLS) data. The MLS data include 3-D point clouds and corresponding multi-view images. First, an integrated method, based on a deep learning network and the retro-...

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Veröffentlicht in:	IEEE transactions on intelligent transportation systems 2019-07, Vol.20 (7), p.2550-2565
Hauptverfasser:	You, Changbin, Wen, Chenglu, Wang, Cheng, Li, Jonathan, Habib, Ayman
Format:	Artikel
Sprache:	eng
Schlagworte:	Automobiles Autonomous vehicles Datasets Driving Estimation geo-localization joint 2-D-3-D Landmarks Localization Localization method Machine learning mobile laser scanning (MLS) multi-view images Point cloud Scanning Semantics Shape Signs Three dimensional models Three-dimensional displays Traffic control traffic sign Traffic signs Trajectory Trajectory analysis
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