What is it about?
The random error pattern of point clouds has significant effect on the quality of final 3D model. The magnitude and distribution of random errors should be modelled numerically. This work aims at developing such an anisotropic point error model, specifically for the terrestrial laser scanner (TLS) acquired 3D point clouds.
Featured Image
Why is it important?
Even though the Terrestrial Laser Scanning (TLS) technology provides accurate 3D description of a target object or scene, individual points of the 3D point cloud contains random and gross errors. These errors propagate through processing steps such as pre-processing, registration, integration and model generation. This fact evokes the question of how reliable the laser scanning data which is widely used for applications vary from cultural heritage to deformation monitoring.
Perspectives
An anisotropic point error model was presented for TLS derived point clouds. First the practical method for angular precision determination was described. Then, range precision was defined empirically as a function of sensor-to-object distance, incidence angle and surface reflectance. It was shown that this empirical function is capable of determining the range precision feasibly. Using these a-priori precision values, the variance and covariance propagation rule was employed for the computation of error ellipsoids for each point.
Dr Devrim AKCA
Isik University
Read the Original
This page is a summary of: AN EMPRICAL POINT ERROR MODEL FOR TLS DERIVED POINT CLOUDS, June 2016, Copernicus GmbH,
DOI: 10.5194/isprs-archives-xli-b5-557-2016.
You can read the full text:
Contributors
The following have contributed to this page
