This paper proposes two robust statistical techniques for outlier detection and robust
saliency features, such as surface normal and curvature, estimation in laser scanning 3D …

Edges provide important visual information in scene surfaces. The need for fast and robust
feature extraction from 3D data is nowadays fostered by the widespread availability of cheap …

This paper proposes robust methods for local planar surface fitting in 3D laser scanning
data. Searching through the literature revealed that many authors frequently used Least …

In recent years, Convolutional Neural Networks (CNN) have proven to be efficient analysis
tools for processing point clouds, eg, for reconstruction, segmentation, and classification. In …

Existing approaches that extract buildings from point cloud data do not select the
appropriate neighbourhood for estimation of normals on individual points. However, the …

Feature-preserving filtering of noisy point clouds plays a fundamental role in geometric
processing. Though the guided filter is known to be a powerful tool for edge-aware image …

Gap and flush measurement is a challenging task in the process of aircraft assembly, which
significantly affects the reliability of aircraft aerodynamic shape. To ensure the quality of …

Given a curvilinear profile P represented as a set of points in the space R 3 and four families
of low-degree polynomial curves that respectively depend on the parameters in the space R …

Abstract 3D geometric features represent rich details of 3D models, whose scale is much
larger than noise. Traditional point cloud denoising methods cannot handle the task of …

Extracting high-level structural information from 3D point clouds is challenging but essential
for tasks like urban planning or autonomous driving requiring an advanced understanding of …