Abstract.
The paper presents an iterative matching method to improve a direct geo-referencing approach for stationary terrestrial 3D laser scans by means of the positional and transformational uncertainties of two 3D point clouds. In this approach, a geo-referenced point cloud from a station inherits the following stochastic information: (1) transformational uncertainties from processed GNSS data through the Kalman filter and (2) positional uncertainties through the range and angular uncertainties from the terrestrial laser scanner as well as the incident angle of the laser beam to a surface. This stochastic information from two (pre-) geo-referenced 3D point clouds is implemented within a novel iterative matching algorithm, named Geo-referencing ICP with Helmert 3D transformation, for subsequent post-processing procedures such as segmentation and further calibration.
© 2012 by Walter de Gruyter Berlin Boston
Articles in the same Issue
- Preface to the special issue on multi-sensor systems in engineering geodesy and navigation
- Performance of deeply integrated GPS/INS in dense forestry areas
- GNSS precise point positioning in regional reference frames using real-time broadcast corrections
- Measurement uncertainty in network RTK GNSS-based positioning of a terrestrial laser scanner
- Geo-referencing point clouds with transformational and positional uncertainties
- Indoor locating and inventory management based on RFID-Radar detecting data
- GNSS-based multi-sensor system for structural monitoring applications
Articles in the same Issue
- Preface to the special issue on multi-sensor systems in engineering geodesy and navigation
- Performance of deeply integrated GPS/INS in dense forestry areas
- GNSS precise point positioning in regional reference frames using real-time broadcast corrections
- Measurement uncertainty in network RTK GNSS-based positioning of a terrestrial laser scanner
- Geo-referencing point clouds with transformational and positional uncertainties
- Indoor locating and inventory management based on RFID-Radar detecting data
- GNSS-based multi-sensor system for structural monitoring applications