Registration of Terrestrial Laser Point Clouds by Fusing Semantic Features and GPS positions

Abstract

Abstract:

Registration is an inevitable process during the procedure of point cloud processing, while point based registration has been the bottleneck of the whole point cloud processing procedure, and pure data driven points matching methods demand strict conditions for the overlapping regions between base and registration stations. This article proposes a new registration method for terrestrial laser point clouds by fusing semantic features and GPS positions. First, the semantic features such as ground and wall fa?ade are automatically recognized using knowledge, then together with GPS positions of the scan station, two point clouds can be roughly registered, and followed by a fine tuning using ICP which minimizes point to plane distance. Two test cases indicate that this method achieves higher registration efficiency for terrestrial laser point clouds, and is especially applicable to scenes containing planar structures such as roads and buildings.

Key words: Registration, laser point clouds, feature extraction, segmentation

CLC Number:

P232

References

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