Buchumschlag

A review of non-rigid transformations and learning-based 3D point cloud registration methods

Point cloud registration is a research field where the spatial relationship between two or more sets of points in space is determined. Point clouds are found in multiple applications, such as laser scanning, 3D reconstruction, and time-of-flight imaging, to mention a few. This paper provides a thoro...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Hauptverfasser: Monji Azad, Sara (VerfasserIn) , Hesser, Jürgen (VerfasserIn) , Löw, Nikolas (VerfasserIn)
Dokumenttyp: Article (Journal)
Sprache:Englisch
Veröffentlicht: February 2023
In: ISPRS journal of photogrammetry and remote sensing
Year: 2023, Jahrgang: 196, Pages: 58-72
ISSN:0924-2716
DOI:10.1016/j.isprsjprs.2022.12.023
Online-Zugang:Verlag, lizenzpflichtig, Volltext: https://doi.org/10.1016/j.isprsjprs.2022.12.023
Verlag, lizenzpflichtig, Volltext: https://www.sciencedirect.com/science/article/pii/S0924271622003380
Volltext
Verfasserangaben:Sara Monji-Azad, Jürgen Hesser, Nikolas Löw
Beschreibung
Zusammenfassung:Point cloud registration is a research field where the spatial relationship between two or more sets of points in space is determined. Point clouds are found in multiple applications, such as laser scanning, 3D reconstruction, and time-of-flight imaging, to mention a few. This paper provides a thorough overview of recent advances in learning-based 3D point cloud registration methods with an emphasis on non-rigid transformations. In this respect, the available studies should take various challenges like noise, outliers, different deformation levels, and data incompleteness into account. Therefore, a comparison study on the quantitative assessment metrics and robustness of different approaches is discussed. Furthermore, a comparative study on available datasets is reviewed. This information will help to understand the new range of possibilities and to inspire future research directions.
Beschreibung:Gesehen am 16.03.2023
Beschreibung:Online Resource
ISSN:0924-2716
DOI:10.1016/j.isprsjprs.2022.12.023

Ähnliche Einträge