Visual-inertia system with dynamic line feature extraction algorithm

Qingyuan Zhao; Xianghua Ma

doi:10.1117/12.3012488

21 December 2023 Visual-inertia system with dynamic line feature extraction algorithm

Qingyuan Zhao, Xianghua Ma

Proceedings Volume 12970, Fourth International Conference on Signal Processing and Computer Science (SPCS 2023); 129702F (2023) https://doi.org/10.1117/12.3012488
Event: Fourth International Conference on Signal Processing and Computer Science (SPCS 2023), 2023, Guilin, China

Abstract

In response to the problem of decreased robustness and accuracy in visual inertial systems due to the inability to extract sufficient point features in weak-textured environments, a dynamic line feature algorithm is proposed, adding the number of co-visible point features as a dynamic threshold to adjust the line feature extraction process. Line features are easier to track in weak-textured environments, providing more geometric information and improving system robustness. The backend utilizes a sliding window algorithm to establish an objective function and jointly optimize the visual-inertial information to improve system accuracy. Experimental results using publicly available datasets demonstrate that compared to the VINS-Mono system, the algorithm exhibits better accuracy and robustness under weak-textured environments.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Qingyuan Zhao and Xianghua Ma "Visual-inertia system with dynamic line feature extraction algorithm", Proc. SPIE 12970, Fourth International Conference on Signal Processing and Computer Science (SPCS 2023), 129702F (21 December 2023); https://doi.org/10.1117/12.3012488

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