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Automatic Registration of Terrestrial Laser Scanning Point Clouds using Panoramic Reflectance Images. | LitMetric

AI Article Synopsis

  • This paper introduces a method for automatically registering terrestrial laser scanning (TLS) point clouds by using panoramic reflectance images.
  • The process involves two main steps: pair-wise registration, which matches images and point clouds, and global registration to align all point clouds using a bundle adjustment technique.
  • The results demonstrate that the method achieves high accuracy, with pair-wise registration accurate to within millimeters and global registration within centimeters, and it operates quickly and fully automatically.

Article Abstract

This paper presents a new approach to the automatic registration of terrestrial laser scanning (TLS) point clouds using panoramic reflectance images. The approach follows a two-step procedure that includes both pair-wise registration and global registration. The pair-wise registration consists of image matching (pixel-to-pixel correspondence) and point cloud registration (point-to-point correspondence), as the correspondence between the image and the point cloud (pixel-to-point) is inherent to the reflectance images. False correspondences are removed by a geometric invariance check. The pixel-to-point correspondence and the computation of the rigid transformation parameters (RTPs) are integrated into an iterative process that allows for the pair-wise registration to be optimised. The global registration of all point clouds is obtained by a bundle adjustment using a circular self-closure constraint. Our approach is tested with both indoor and outdoor scenes acquired by a FARO LS 880 laser scanner with an angular resolution of 0.036° and 0.045°, respectively. The results show that the pair-wise and global registration accuracies are of millimetre and centimetre orders, respectively, and that the process is fully automatic and converges quickly.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3348833PMC
http://dx.doi.org/10.3390/s90402621DOI Listing

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