Infrared target 3D reconstruction based on TRC-MVSNet

Hua Gong; Tan Jin; Shuwei Tang; Yuanjing Ma

doi:10.1117/12.3025485

28 February 2024 Infrared target 3D reconstruction based on TRC-MVSNet

Hua Gong, Tan Jin, Shuwei Tang, Yuanjing Ma

Proceedings Volume 13071, International Conference on Mechatronic Engineering and Artificial Intelligence (MEAI 2023); 130712S (2024) https://doi.org/10.1117/12.3025485
Event: International Conference on Mechatronic Engineering and Artificial Intelligence (MEAI 2023), 2023, Shenyang, China

Abstract

A 3D reconstruction network, TRC-MVSNet, is proposed to address the issue of poor 3D reconstruction of infrared multi-view. It combines Transformer feature matching and RC-MVSNet. To enhance the quality of the infrared image, a moving average filter method is employed to mitigate noise by averaging signals in a sliding window. Additionally, the Transformer network is utilized to improve the matching quality of infrared multi-view information by matching the information of multiple infrared views in the feature matching stage. Experimental results demonstrate that the TRCMVSNet 3D reconstruction model enhances accuracy by 0.03 and synthesis by 0.013 compared to the RC-MVSNet 3D reconstruction model on the DTU dataset. The TRC-MVSNet achieves high accuracy, efficiency, and minimal noise in the 3D reconstruction of infrared targets on the SYLU-IMD dataset, outperforming other methods.

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

Citation Download Citation

Hua Gong, Tan Jin, Shuwei Tang, and Yuanjing Ma "Infrared target 3D reconstruction based on TRC-MVSNet", Proc. SPIE 13071, International Conference on Mechatronic Engineering and Artificial Intelligence (MEAI 2023), 130712S (28 February 2024); https://doi.org/10.1117/12.3025485

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KEYWORDS

3D modeling

Infrared radiation

Infrared imaging

Data modeling

Point clouds

Transformers

Visual process modeling

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