Performance Assessment of Neural Radiance Fields (NeRF) and Photogrammetry for 3D Reconstruction of Man-Made and Natural Features

Abhinav Polimera, M. Mohan, K. Rajitha

2024

Abstract

The present study focuses on the reconstruction of 3D models of an antenna (man-made) and a bush (natural feature) by adopting the recently developed Neural Radiance Fields (NeRF) technique of deep learning. The performance of the NeRF was compared with the outcomes obtained by the traditional photogrammetry methods. The ground truth geometric observation of the selected objects derived using electronic distance measurement-based techniques revealed the efficacy of NeRF compared to photogrammetry for both man-made and natural features’ reconstruction cases. The capabilities of NeRF to reconstruct the features with complex geometries were evident from the outcome of bush 3D reconstruction. The prospectus of canopy and leaf level geometry estimation using NeRF will aid the enhanced modeling of vegetation-atmosphere interactions. The findings presented in the study have significant implications for diverse fields, from entertainment to ecological modeling, and offer insights into the practical applications of NeRF in 3D reconstruction. The outcomes of the present study attempted with a texture-less object like a bush unveiled the opportunities to apply the NeRF techniques in precision agriculture.

Paper Citation

in Harvard Style

Polimera A., Mohan M. and Rajitha K. (2024). Performance Assessment of Neural Radiance Fields (NeRF) and Photogrammetry for 3D Reconstruction of Man-Made and Natural Features. In Proceedings of the 16th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART; ISBN 978-989-758-680-4, SciTePress, pages 840-847. DOI: 10.5220/0012396700003636

in Bibtex Style

@conference{icaart24,
author={Abhinav Polimera and M. Mohan and K. Rajitha},
title={Performance Assessment of Neural Radiance Fields (NeRF) and Photogrammetry for 3D Reconstruction of Man-Made and Natural Features},
booktitle={Proceedings of the 16th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART},
year={2024},
pages={840-847},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012396700003636},
isbn={978-989-758-680-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 16th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART
TI - Performance Assessment of Neural Radiance Fields (NeRF) and Photogrammetry for 3D Reconstruction of Man-Made and Natural Features
SN - 978-989-758-680-4
AU - Polimera A.
AU - Mohan M.
AU - Rajitha K.
PY - 2024
SP - 840
EP - 847
DO - 10.5220/0012396700003636
PB - SciTePress