Application of Photogrammetry to Gaussian Splatting for mesh and texture reconstruction

Bachelor Thesis (2024)
Author(s)

K.J. Kiisa (TU Delft - Electrical Engineering, Mathematics and Computer Science)

Contributor(s)

X. Zhang – Mentor (TU Delft - Pattern Recognition and Bioinformatics)

M. Weinmann – Graduation committee member (TU Delft - Computer Graphics and Visualisation)

Faculty
Electrical Engineering, Mathematics and Computer Science
More Info
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Publication Year
2024
Language
English
Graduation Date
25-06-2024
Awarding Institution
Delft University of Technology
Project
['CSE3000 Research Project']
Programme
['Computer Science and Engineering']
Faculty
Electrical Engineering, Mathematics and Computer Science
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Abstract

Gaussian Splatting is a successful recent method for generating novel views of a scene based on photographs taken from that scene [1]. It uses rasterization in order to render the scenes it generates, which consist of 3D Gaussians. However, modern hardware and tools are designed and optimized around rendering polygonal and texture based models [2]. This paper proposes a method of extracting both a 3D model and texture file from a Gaussian Splatting scene by using renders of that scene in Photogrammetry. It shows that this can be a viable method for generating a traditional 3D model from Gaussian Splatting scene, and can for certain cases generate a model of comparable quality while lowering the number of initial images required by up to three times.

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