UAV images three-dimensional reconstruction based on neural radiance fields

Shijie Wang; Jicheng Meng

doi:10.1117/12.3031072

19 July 2024 UAV images three-dimensional reconstruction based on neural radiance fields

Shijie Wang, Jicheng Meng

Proceedings Volume 13181, Third International Conference on Electronic Information Engineering, Big Data, and Computer Technology (EIBDCT 2024); 1318122 (2024) https://doi.org/10.1117/12.3031072
Event: Third International Conference on Electronic Information Engineering, Big Data, and Computer Technology (EIBDCT 2024), 2024, Beijing, China

Abstract

This paper investigates the three-dimensional reconstruction technique of unmanned aerial vehicle (UAV) images under multiscale scenarios based on neural radiance fields. The approach combines the concept of residual networks and the convergence method of unbounded region functions, and its feasibility is demonstrated through theoretical analysis. Experimental studies are conducted on UAV image datasets at various scales, with a particular focus on unbounded regions with diverse camera poses. The proposed model achieves satisfactory results in handling the challenges posed by multiscale UAV image data.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Shijie Wang and Jicheng Meng "UAV images three-dimensional reconstruction based on neural radiance fields", Proc. SPIE 13181, Third International Conference on Electronic Information Engineering, Big Data, and Computer Technology (EIBDCT 2024), 1318122 (19 July 2024); https://doi.org/10.1117/12.3031072

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available