Searched for: subject:"Point%5C+cloud"
(1 - 20 of 151)

Pages

document
Widyaningrum, E. (author)
A base map provides essential geospatial information for applications such as urban planning, intelligent transportation systems, and disaster management. Buildings and roads are the main ingredients of a base map and are represented by polygons. Unfortunately, manually delineating their boundaries from remote sensing data is time consuming and...
doctoral thesis 2021
document
Papalexiou, Annie (author)
Although monitoring and maintenance of railways is important to ensure safety and avoid delays and financial losses, it is still mainly based on human inspection. The complexity of a railway along with the large area it extends makes manual monitoring difficult and time-consuming. The increasing availability of 3D acquisition technologies has...
master thesis 2021
document
Zang, Y. (author), Meng, Fancong (author), Lindenbergh, R.C. (author), Truong-Hong, Linh (author), Li, Bijun (author)
Mobile laser scanning (MLS) systems are often used to efficiently acquire reference data covering a large-scale scene. The terrestrial laser scanner (TLS) can easily collect high point density data of local scene. Localization of static TLS scans in mobile mapping point clouds can afford detailed geographic information for many specific tasks...
journal article 2021
document
Truong-Hong, Linh (author), Lindenbergh, R.C. (author)
A three-dimensional (3D) geometric model of a bridge plays an important role in inspection, assessment and management of the bridge. As most bridges were built after the second world war, 3D bridge models are rarely available. A recent development in laser scanning offers a cost-efficient method to capture dense, accurate 3D topographic data...
book chapter 2021
document
Widyaningrum, E. (author), Bai, Q. (author), Fajari, Marda K. (author), Lindenbergh, R.C. (author)
Classification of aerial point clouds with high accuracy is significant for many geographical applications, but not trivial as the data are massive and unstructured. In recent years, deep learning for 3D point cloud classification has been actively developed and applied, but notably for indoor scenes. In this study, we implement the point-wise...
journal article 2021
document
Meng, Fancong (author)
Localization is a problem of ’where we are’. Localization techniques help people understand their surrounding environment based on extracted position information in a geographic reference map. The development of global navigation satellite system (GNSS), light detection and ranging (LiDAR), computer vision (CV), etc., enables us to apply...
master thesis 2020
document
Deng, Mutian (author)
This research is aimed to answer the main research question: to what extent we can use LiDAR point clouds directly in the PostgreSQL by means of FDW, and thus a FDW supporting the Point Cloud Data Management System is implemented. Then, the range and performance of its functionality are evaluated. The results shows this FDW solution is feasible...
master thesis 2020
document
Zhang, Liyao (author)
Visualizing the point clouds is an integral part of processing the data, which enables users to explore and interact with the point clouds more intuitively. However, most of the current point cloud renderers are developed in non-immersive environments. In the last few years, some new technologies, such as Augmented Reality (AR), Virtual Reality ...
master thesis 2020
document
Rustici, Pietro (author)
This study investigates whether an automatic anonymization algorithm that takes as input a 3D model of a human face can produce an output model exempt from General Data Protection Regulation (GDPR) biometric data definition. The algorithm first uses Random Sample Consensus (RANSAC) for registering the source point cloud globally to an oriented...
bachelor thesis 2020
document
van der Sluis, Joram (author)
This master thesis presents an experimental study on 3D person localization (i.e., pedestrians, cyclists)in traffic scenes, using monocular vision and Light Detection And Ranging (LiDAR) data. The performance of two top-ranking methods is analyzed on the 3D object detection KITTI dataset. In this evaluation, the effect of the Intersection over...
master thesis 2020
document
Dekker, Quinten (author)
Dense 3D modeling based on monocular visual data is a powerful process of gaining spatial 3D understanding from 2D observations. The use of visual data to reconstruct such 3D models is still a challenging topic. To obtain the accurate dimensions, additional metadata is required such as a GPS which is not always available. Besides this, dealing...
master thesis 2020
document
Balado Frías, J. (author), González, E. (author), Verbree, E. (author), Díaz-Vilarino, L. (author), Lorenzo, H. (author)
Occlusions accompany serious problems that reduce the applicability of numerous algorithms. The aim of this work is to detect and characterize urban ground gaps based on occluding object. The point clouds for input have been acquired with Mobile Laser Scanning and have been previously segmented into ground, buildings and objects, which have...
journal article 2020
document
Alexandridis, Vasileios (author)
Bathymetric Airborne LiDAR technology is used to map the depth of water bodies. It uses a green light sensor which is able to penetrate the water surface and reach the bottom part of the interesting water areas. However, water conditions affect the capability of the green laser penetration. Factors such as the water clarity, the water turbidity ...
master thesis 2020
document
Smit, M. (author), Chen, Z. (author), Erbaşu, M.A. (author), Gaol, Y.A.L. (author), Li, X. (author)
With the constantly evolving range of applications for technology the quality and amount of data constantly increases as well. In this growing data environment, there is a constant search to provide more value to all data that is available for as little effort as possible. Our research tries to add such additional value by diving into the...
student report 2020
document
Bai, Qian (author)
Semantic segmentation of aerial point clouds with high accuracy is significant for many geographical applications, but is not trivial since the data is massive and unstructured. In the past few years, deep learning approaches designed for 3D point cloud data have made great progress. Pointwise neural networks, such as PointNet and its extensions...
student report 2020
document
Garg, Chirag (author)
3D indoor reconstruction has been an important research area in the field of computer vision and photogrammetry. While the initial techniques developed for this purpose use sensor devices and multiple images for data acquisition and extracting 3D information and representation of the scene, with the advent of deep learning techniques, there has...
master thesis 2020
document
Oostwegel, Laurens (author)
Unlike outdoor environments, there is no wide-spread solution to positioning inside a building. Indoorsolutions rely on pre-installation of infrastructure, such as Bluetooth beacons or ultra-wide bandtechnology. Recently, there has been growing interest in the use of Augmented Reality (AR) for indoorpositioning. AR devices use an algorithm known...
master thesis 2020
document
Dahle, Felix (author)
In many countries digital maps are created and provided by the national cadastres: Usually they consist of multiple polygons, each with an exact location and shape, describing which kind of surface can be found at the position of the polygon (e. g. building, street, vegetation). They must be accurate and well maintained, as they are used by...
master thesis 2020
document
Alkadri, M.F. (author), De Luca, Francesco (author), Turrin, M. (author), Sariyildiz, I.S. (author)
As a passive design strategy, solar envelopes play a significant role in determining building mass based on desirable sun access during a predefined period. Nowadays, advancements in the area of computational tools permit designers to develop new methods for establishing solar envelopes. However, current approaches lack an understanding of the...
journal article 2020
document
Liu, H. (author), van Oosterom, P.J.M. (author), Meijers, B.M. (author), Verbree, E. (author)
Dramatically increasing collection of point clouds raises an essential demand for highly efficient data management. It can also facilitate modern applications such as robotics and virtual reality. Extensive studies have been performed on point data management and querying, but most of them concentrate on low dimensional spaces. High...
journal article 2020
Searched for: subject:"Point%5C+cloud"
(1 - 20 of 151)

Pages