University of Twente Student Theses
Exploiting shadows to infer 3D structures
Gadelmawla, Omar (2022) Exploiting shadows to infer 3D structures.
|
PDF
11MB |
| Abstract: | Buildings and vegetation height estimation using remotely sensed images are challenging to achieve. However, effective solutions to this challenge can serve in tackling more complex problems in the remote sensing field that require 3D information about objects in aerial images, which might be costly or inaccessible. Because shadows are a standard metric among many architectural building designs worldwide, shadows can help infer 3D structures as an auxiliary input in Deep Learning (DL) models. This paper proposes a method to combine RGB aerial imagery and height maps extracted from Light Detection And Ranging (LiDAR) sensors to develop an effective algorithm to realistically exaggerate shadow areas in RGB aerial imagery to enhance the learning process of the DL model. The results suggest that the proposed method is an effective solution for the problem, given the evaluation metrics specified in the paper. |
| Item Type: | Essay (Bachelor) |
| Faculty: | EEMCS: Electrical Engineering, Mathematics and Computer Science |
| Subject: | 54 computer science |
| Programme: | Computer Science BSc (56964) |
| Link to this item: | https://purl.utwente.nl/essays/92022 |
| Export this item as: | BibTeX EndNote HTML Citation Reference Manager |
Show download statistics for this publication
Show download statistics for this publicationRepository Staff Only: item control page