Searched for: subject:"point%5C+cloud"
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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Wu, Teng (author)
This thesis proposes a novel medial axis transform (MAT) based method to achieve visibility analysis in a point cloud. There are several advantages of this MAT based method. This method avoids surface reconstruction from a point cloud. It also works for the situation when there is surface missing in the input point cloud. For different point...
master thesis 2019
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Islam, Hanif Dinul (author)
More than 30% of the world’s hydrocarbon reserves are located in carbonate reservoirs, and this percentage is likely to increase, as a result of discoveries of new giant oil fields in carbonate rocks, generically named “Pre-salt layers”. However, there are still some problems in understanding karst systems that still unresolved. The karst caves...
master thesis 2019
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Ai, Zhiwei (author)
Deep learning methods have been demonstrated to be promising in semantic segmentation of point clouds. Existing works focus on extracting informative local features based on individual points and their local neighborhood. They lack consideration of the general structures and latent contextual relations of underlying shapes among points. To this...
master thesis 2019
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Anastasiadou, Anastasia (author)
Over the last decades, laser scanners are becoming more and more established for the acquisition of geo-information. Depending on the sensor platform where the laser scanners are mounted, there are MLS, ALS and TLS techniques for both indoor and outdoor environments. The high-quality 3D point clouds produced from laser scanners is an important...
master thesis 2019
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Ruben, Pablo (author)
Recently, the application of machine learning and data fusion techniques on hyperspectral imagery have demonstrated potential for ground cover classification at material level. Hereby, specific locations of resources enclosed in cities (e.g. roof materials) can be identified, which is critically relevant within the field of urban mining. A...
master thesis 2019
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Sassen, Tom (author)
In 2017 the Netherlands had 7146km of railways [Ramaekers et al., 2009], which are owned and managed by ProRail and have to be frequently surveyed, for quality inspection. Surveying is done using a variety of surveying techniques, many of which require surveyors to walk on or near the tracks, which could cause injuries. An alternative surveying...
master thesis 2019
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Du, Shenglan (author)
Trees are of great significance throughout the world, both in urban scenes and in natural environments. Models of trees can be widely applied in various fields, for instance, landscape design, geo-simulation, environment modelling, and forestry inventories. Recently, laser scanning technology has been rapidly developed, making it possible to...
master thesis 2019
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Wang, Qu (author)
This project develop a new method to generate breakline from the point cloud directly with the MAT. The breakline is a structured line of the object surface which has high curvature. Meanwhile, the reciprocal of the medial edge ball's radius can represent the point with high curvature, which is the fundamental idea of this project. The key parts...
master thesis 2019
Searched for: subject:"point%5C+cloud"
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