Lehtola, Ville

Advances in Mobile Mapping Technologies - Basel MDPI - Multidisciplinary Digital Publishing Institute 2022 - 1 electronic resource (268 p.)

Open Access

Mobile mapping is applied widely in society, for example, in asset management, fleet management, construction planning, road safety, and maintenance optimization. Yet, further advances in these technologies are called for. Advances can be radical, such as changes to the prevailing paradigms in mobile mapping, or incremental, such as the state-of-the-art mobile mapping methods. With current multi-sensor systems in mobile mapping, laser-scanned data are often registered in point clouds with the aid of global navigation satellite system (GNSS) positioning or simultaneous localization and mapping (SLAM) techniques and then labeled and colored with the aid of machine learning methods and digital camera data. These multi-sensor platforms are beginning to undergo further advancements via the addition of multi-spectral and other sensors and via the development of machine learning techniques used in processing this multi-modal data. Embedded systems and minimalistic system designs are also attracting attention, from both academic and commercial perspectives.This book contains the accepted publications of the Special Issue 'Advances in Mobile Mapping Technologies' of the Remote Sensing journal. It consists of works introducing a new mobile mapping dataset (‘Paris CARLA 3D’), system calibration studies, SLAM topics, and multiple deep learning works for asset detection. We, the Guest Editors, Ville Lehtola from University of Twente, Netherlands, Andreas Nüchter from University of Würzburg, Germany, and François Goulette from Mines Paris- PSL University, France, wish to thank all the authors who contributed to this collection.


Creative Commons


English

9783036534909 9783036534893


Мобильные приложения

LiDAR RetinaNet inception Mobile Laser Scanning point clouds data fusion Lidar point cloud density point cloud coverage mobile mapping systems 3D simulation Pandar64 Ouster OS-1-64 mobile laser scanning lever arm boresight angles plane-based calibration field configuration analysis accuracy controllability evaluation control points TLS reference point clouds visual–inertial odometry Helmert variance component estimation line feature matching method correlation coefficient point and line features mobile mapping manhole cover point cloud F-CNN transfer learning CAM localization loop closure detection visual SLAM semantic topology graph graph matching CNN features deep learning view planning imaging network design building 3D modelling path planning V-SLAM real-time guidance embedded-systems 3D surveying exposure control photogrammetry parking statistics vehicle detection robot operating system 3D camera RGB-D performance evaluation convolutional neural networks smart city georeferencing MSS IEKF DSIEKF geometrical constraints 6-DoF DTM 3D city model dataset laser scanning 3D mapping synthetic outdoor semantic scene completion

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