University of Twente Student Theses

Login

Point Cloud Digital Terrain Modeling from Video Data in Rail Environment

Dylewski, Artur (2024) Point Cloud Digital Terrain Modeling from Video Data in Rail Environment.

[img] PDF
6MB
Abstract:Digital Elevation Models (DEM), represent the topography of the bare Earth and can be processed using computer software. These models are often utilized in industries such as transportation and engineering for creating digital twins and ensuring the efficient operation of machinery and infrastructure. This paper discusses the methodology for generating Digital Terrain Models (DTMs) within rail infrastructure using monocular video footage. DTMs being DEMs that exclude man-made infrastructure and vegetation. The techniques covered include GPS interpolation, feature matching and extraction, triangulation, and computer vision models for converting DEMs into DTMs. The generation and comparison of point clouds are demonstrated, showing acceptable accuracy for given context. The results indicate that this technology has potential for low to medium accuracy use cases, though it has certain limitations that are discussed. The paper covers the technical challenges and solutions associated with this approach and compares its characteristics to the current standard, LIDAR. The main takeaway for future research is that this method is a viable alternative to LIDAR, but achieving high accuracy requires significant effort in setting up high-quality systems and using more reliable object detection models with more training data. Additional Key Words and Phrases: Digital terrain model, Point Cloud, Video topography extraction
Item Type:Essay (Bachelor)
Faculty:EEMCS: Electrical Engineering, Mathematics and Computer Science
Subject:54 computer science
Programme:Business & IT BSc (56066)
Link to this item:https://purl.utwente.nl/essays/101108
Export this item as:BibTeX
EndNote
HTML Citation
Reference Manager

 

Repository Staff Only: item control page