Abstract
The paper presents analysis of the orientation of terrestrial laser scanning (TLS) data. In the proposed data processing methodology, point clouds are considered as panoramic images enriched by the depth map. Computer vision (CV) algorithms are used for orientation, which are applied for testing the correctness of the detection of tie points and time of computations, and for assessing difficulties in their implementation. The BRISK, FASRT, MSER, SIFT, SURF, ASIFT and CenSurE algorithms are used to search for key-points. The source data are point clouds acquired using a Z+F 5006h terrestrial laser scanner on the ruins of Iłża Castle, Poland. Algorithms allowing combination of the photogrammetric and CV approaches are also presented.
Highlights
Point clouds are acquired from terrestrial laser scanning (TLS) in a local reference system of the instrument
Methods which utilize detectors and 3D descriptors of key-points are used (Theiler et al, 2013; Theiler et al, 2014.). Another approach which is applied for point cloud orientation uses raster images, generated on the basis of TLS data, and successive image processing algorithms, applied using the computer vision (CV) method for identification of tie points
Following the distribution of errors on control points, it may be stated that the MSER, shortest processing time was with the CenSurE (STAR), BRISK, SURF, SIFT and ASIFT algorithms are characterized by similar values of errors
Summary
Point clouds are acquired from terrestrial laser scanning (TLS) in a local reference system of the instrument. For a large number of data sets (where big and complex objects are processed),the point clouds need to be transformed for a global reference system. This process consists of determination of orientation parameters, i.e.,three angles of rotation and three elements of linear transformation. Methods which utilize detectors and 3D descriptors of key-points are used (Theiler et al, 2013; Theiler et al, 2014.) Another approach which is applied for point cloud orientation uses raster images, generated on the basis of TLS data, and successive image processing algorithms, applied using the computer vision (CV) method for identification of tie points. Target-based analysis is compared with the transformed feature-based registration method
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