loading
Papers Papers/2022 Papers Papers/2022

Research.Publish.Connect.

Paper

Authors: Abhinav Polimera ; M. Mohan and K. Rajitha

Affiliation: Birla Intitute of Technology and Science Pilani, Hyderabad Campus, India

Keyword(s): Neural Radiance Fields (NeRF), Photogrammetry, 3D Reconstruction, Ecological Modeling.

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 pr actical 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. (More)

CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 3.147.85.183

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
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; ISSN 2184-433X, SciTePress, pages 840-847. DOI: 10.5220/0012396700003636

@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},
issn={2184-433X},
}

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
IS - 2184-433X
AU - Polimera, A.
AU - Mohan, M.
AU - Rajitha, K.
PY - 2024
SP - 840
EP - 847
DO - 10.5220/0012396700003636
PB - SciTePress

- Science and Technology Publications, Lda.
RESOURCES

Proceedings

Papers

Authors

Ontology

CONTACTS

Science and Technology Publications, Lda
Avenida de S. Francisco Xavier, Lote 7 Cv. C,
2900-616 Setúbal, Portugal.

Phone: +351 265 520 185 (National fixed network call)
Fax: +351 265 520 186
Email: info@scitepress.org

EXTERNAL LINKS

PRIMORIS

INSTICC

SCITEVENTS

CROSSREF

PROCEEDINGS SUBMITTED FOR INDEXATION BY:

dblp

Ei Compendex

SCOPUS

Semantic Scholar

Google Scholar

Microsoft Academic