INCREMENTAL MAP REFINEMENT OF BUILDING INFORMATION USING LIDAR POINT CLOUDS
For autonomous systems, an accurate and precise map of the environment is of importance. Mapping from LiDAR point clouds is one of the promising ways to generate 3D environment models. However, there are many problems caused by inaccurate data, missing areas, low density of points and sensor noise....
Main Authors: | Q. Zou, M. Sester |
---|---|
Format: | Article |
Language: | English |
Published: |
Copernicus Publications
2021-06-01
|
Series: | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
Online Access: | https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLIII-B2-2021/277/2021/isprs-archives-XLIII-B2-2021-277-2021.pdf |
Similar Items
-
MAPPING BUILDING INTERIORS WITH LIDAR: CLASSIFYING THE POINT CLOUD WITH ARCGIS
by: J. R. Parent, et al.
Published: (2021-08-01) -
INCREMENTAL REFINEMENT OF FAÇADE MODELS WITH ATTRIBUTE GRAMMAR FROM 3D POINT CLOUDS
by: Y. Dehbi, et al.
Published: (2016-06-01) -
Learning the Incremental Warp for 3D Vehicle Tracking in LiDAR Point Clouds
by: Shengjing Tian, et al.
Published: (2021-07-01) -
SURFACE FITTING FILTERING OF LIDAR POINT CLOUD WITH WAVEFORM INFORMATION
by: S. Xing, et al.
Published: (2017-09-01) -
SEMANTIC LABELING AND REFINEMENT OF LIDAR POINT CLOUDS USING DEEP NEURAL NETWORK IN URBAN AREAS
by: R. Huang, et al.
Published: (2019-09-01)