A point cloud filtering method based on anisotropic error model
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Tarih
2023-12
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
John Wiley and Sons Inc
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
Many modelling applications require 3D meshes that should be generated from filtered/cleaned point clouds. This paper proposes a methodology for filtering of terrestrial laser scanner (TLS)-derived point clouds, consisting of two main parts: an anisotropic point error model and the subsequent decimation steps for elimination of low-quality points. The point error model can compute the positional quality of any point in the form of error ellipsoids. It is formulated as a function of the angular/mechanical stability, sensor-to-object distance, laser beam's incidence angle and surface reflectivity, which are the most dominant error sources. In a block of several co-registered point clouds, some parts of the target object are sampled by multiple scans with different positional quality patterns. This situation results in redundant data. The proposed decimation steps removes this redundancy by selecting only the points with the highest positional quality. Finally, the Good, Bad, and the Better algorithm, based on the ray-tracing concept, was developed to remove the remaining redundancy due to the Moiré effects. The resulting point cloud consists of only the points with the highest positional quality while reducing the number of points by factor 10. This novel approach resulted in final surface meshes that are accurate, contain predefined level of random errors and require almost no manual intervention.
Açıklama
This study was supported by TUBITAK – The Scientific and Technological Research Council of Türkiye (project ID: 115Y239); and the Scientific Research Projects of Zonguldak Bülent Ecevit University (project ID: 2015‐47912266‐01).
Anahtar Kelimeler
Error ellipsoid, Point clouds, Point error model, Quality evaluation, Surface reconstruction, Terrestrial laser scanning, Anisotropy, Laser applications, Laser beams, Random errors, Seebeck effect, Surveying instruments, Three dimensional computer graphics, Anisotropic errors, Error ellipsoids, Error modeling, Filtering method, Point error model, Point-clouds, Quality evaluation, Remote-sensing, Redundancy, To-plane registration, Consolidation, Calibration, Uncertainty
Kaynak
Photogrammetric Record
WoS Q Değeri
Q3
Scopus Q Değeri
Q2
Cilt
38
Sayı
184
Künye
Özendi, M., Akça, D. & Topan, H. (2023). A point cloud filtering method based on anisotropic error model. Photogrammetric Record, 38(184), 460-497. doi:10.1111/phor.12460
