Abstract
The faithful 3D reconstruction of urban environments is an important prerequisite for tasks such as city modeling, scene interpretation or urban accessibility analysis. Typically, a dense and accurate 3D reconstruction is acquired with terrestrial laser scanning (TLS) systems by capturing several scans from different locations, and the respective point clouds have to be aligned correctly in a common coordinate frame. In this paper, we present an accurate and robust method for a keypoint-based registration of unordered point clouds via projective scan matching. Thereby, we involve a consistency check which removes unreliable feature correspondences and thus increases the ratio of inlier correspondences which, in turn, leads to a faster convergence of the RANSAC algorithm towards a suitable solution. This consistency check is fully generic and it not only favors geometrically smooth object surfaces, but also those object surfaces with a reasonable incidence angle. We demonstrate the performance of the proposed methodology on a standard TLS benchmark dataset and show that a highly accurate and robust registration may be achieved in a fully automatic manner without using artificial markers.
Original language | English |
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Pages (from-to) | 89-96 |
Number of pages | 8 |
Journal | ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
Volume | 2 |
Issue number | 3W5 |
DOIs | |
State | Published - 19 Aug 2015 |
Externally published | Yes |
Event | ISPRS Geospatial Week 2015 - La Grande Motte, France Duration: 28 Sep 2015 → 3 Oct 2015 |
Keywords
- Feature extraction
- Filtering
- Imagery
- Laser scanning
- Matching
- Point cloud
- Registration
- TLS