Rapid extraction of pavement aggregate gradation based on point clouds using deep learning networks

Usage of asphalt mixture with poor gradation will most likely lead to pavement deficiency. There is a growing need for rapid and non-destructive methods to extract pavement aggregate gradation. In this study, a deep learning-based method that utilizes point clouds data for gradation extraction was proposed. Firstly, a data enhancement...

Towards a digital twin of a storage tank using laser scan data

This paper proposes a methodology to automatically extract components of an oil storage tank from terrestrial laser scanning (TLS) point clouds, and subsequently to create a three-dimensional (3D) solid model of the tank for numerical simulation. The proposed method is integrated into a smart analysis layer of a digital twin platform...

Road type classification of MLS point clouds using deep learning

Functional classification of the road is important to the construction of sustainable transport systems and proper design of facilities. Mobile laser scanning (MLS) point clouds provide accurate and dense 3D measurements of road scenes, while their massive data volume and lack of structure also bring difficulties in processing. 3D point cloud...

Ontology-based semantic conceptualisation of historical built heritage to generate parametric structured models from point clouds

Nowadays, cultural and historical built heritage can be more effectively preserved, val-orised and documented using advanced geospatial technologies. In such a context, there is a major issue concerning the automation of the process and the extraction of useful information from a huge amount of spatial information acquired by means of...

Novel approach to automatic traffic sign inventory based on mobile mapping system data and deep learning

Traffic signs are a key element in driver safety. Governments invest a great amount of resources in maintaining the traffic signs in good condition, for which a correct inventory is necessary. This work presents a novel method for mapping traffic signs based on data acquired with MMS (Mobile Mapping System): images and point clouds. On the...

A parallel N-dimensional Space-Filling Curve library and its application in massive point cloud management

Because of their locality preservation properties, Space-Filling Curves (SFC) have been widely used in massive point dataset management. However, the completeness, universality, and scalability of current SFC implementations are still not well resolved. To address this problem, a generic n-dimensional (nD) SFC library is proposed and...

Automated calibration of fem models using LiDAR point clouds

In present work it is pretended to estimate elastic parameters of beams through the combined use of precision geomatic techniques (laser scanning) and structural behaviour simulation tools. The study has two aims, on the one hand, to develop an algorithm able to interpret automatically point clouds acquired by laser scanning systems of beams...

Image-based method for the pairwise registration of mobile laser scanning point clouds

In this paper, a method is proposed for solving relative translations of 3D point clouds collected by Mobile Laser Scanning (MLS) techniques. The proposed approach uses the attributes of the 3D points to generate and match 2D-projections, by employing a simple correlation technique instead of matching in 3D. As a result, the developed method...

On a knowledge-based approach to the classification of mobile laser scanning point clouds

A knowledge-based system exploits the knowledge, which a human expert uses for completing a complex task, through a database containing decision rules, and an inference engine. Already in the early nineties knowledge-based systems have been proposed for automated image classification. Lack of success faded out initial interest and enthusiasm,...

Classification of mobile laser scanning point clouds of urban scenes exploiting cylindrical neighbourhoods

This paper presents our work on automated classification of Mobile Laser Scanning (MLS) point clouds of urban scenes with features derived from cylinders around points of consideration. The core of our method consists of spanning up a cylinder around points and deriving features, such as reflectance, height difference, from the points present...

Classification of mobile laser scanning point clouds from height features

The demand for 3D maps of cities and road networks is steadily growing and mobile laser scanning (MLS) systems are often the preferred geo-data acquisition method for capturing such scenes. Because MLS systems are mounted on cars or vans they can acquire billions of points of road scenes within a few hours of survey. Manual processing of...

Coarse point cloud registration by EGI matching of voxel clusters

Laser scanning samples the surface geometry of objects efficiently and records versatile information as point clouds. However, often more scans are required to fully cover a scene. Therefore, a registration step is required that transforms the different scans into a common coordinate system. The registration of point clouds is usually conducted...

Accuracy assessment of building point clouds automatically generated from iphone images

Low-cost sensor generated 3D models can be useful for quick 3D urban model updating, yet the quality of the models is questionable. In this article, we evaluate the reliability of an automatic point cloud generation method using multi-view iPhone images or an iPhone video file as an input. We register such automatically generated point cloud...