This paper evaluated the feasibility of a terrestrial point cloud generated utilizing an uncalibrated hand-held consumer camera at a plot level and measuring the plot at an individual-tree level. Individual tree stems in the plot were detected and modeled from the image-based point cloud, and the diameter-at-breast-height (DBH) of each tree was estimated. The detected-results were compared with...

To efficiently handle the continuously increasing raw point data-set sizes from high-resolution laser-range scanning devices or baseline stereo and multi-view 3D object reconstruction systems, powerful geometry processing solutions are required. We present a flexible and run-time configurable system for efficient out-of-core geometry processing of point cloud data that significantly extends and...

The recently developed pure transformer architectures have attained promising accuracy on point cloud learning benchmarks compared to convolutional neural networks. However, existing Transformers are computationally expensive because they waste a significant amount of time structuring irregular data. To solve this shortcoming, we present the Sparse Window Attention module gather coarse-grained ...

In this paper we present a robust orientation approach for an imaging sensor flown on a micro-UAV based on image triplets. Our aim is to have the orientation available online, i.e. during image acquisition. The resulting point cloud and sensor orientations can then for instance be evaluated for navigation purposes of the UAV or to analyse the completeness of the point cloud. We use low quality ...

Three dimensional point cloud data obtained from mobile laser scanning systems commonly contain outliers. In the presence of outliers most of the currently used methods such as principal component analysis for point cloud processing and feature extraction produce inaccurate and unreliable results. This paper investigates the problems of outliers, and explores advantages of recently introduced s...

Point cloud is the most fundamental representation of 3D geometric objects. Analyzing and processing point cloud surfaces is important in computer graphics and computer vision. However, most of the existing algorithms for surface analysis require connectivity information. Therefore, it is desirable to develop a mesh structure on point clouds. This task can be simplified with the aid of a parame...

LiDAR (Light Detection And Ranging) technology is an important means to obtain three-dimensional information of trees and vegetation. However, due the influence scanning mode, environmental occlusion mutual between tree canopies other factors, a point cloud often has different degrees data loss, which affects high-precision quantitative extraction vegetation parameters. Aiming at problem laser ...

Numerous applications processing 3D point data will gain from the ability to estimate reliably normals and differential geometric properties encoding curvature. In general, normal estimation is notoriously unreliable, the errors propagate and lead to unreliable curvature estimates. Frankot-Chellappa introduced the use of integrability constraints in normal estimation. Their approach deals with ...

Light Detection and Ranging (LiDAR), a high-precision technique used for acquiring three-dimensional (3D) surface information, is widely used to study surface vegetation information. Moreover, the extraction of a vegetation point set from the LiDAR point cloud is a basic starting-point for vegetation information analysis, and an important part of its further processing. To extract the vegetatio...

In the past few years, many efficient rendering and surface reconstruction algorithms for point clouds have been developed. However, collision detection of point clouds has not been considered until now, although this is a prerequisite to use them for interactive or animated 3D graphics. We present a novel approach for time-critical collision detection of point clouds. Based solely on the point...