Journal of System Simulation
Abstract
Abstract: To address the issues of sensitivity to texture and lighting variations, excessive local dependence caused by feature point redundancy, and storage overhead under hardware resource constraints in existing VSLAM feature extractors in indoor environments, We propose the Texture- Oriented and Homogenized FAST Feature Extractor (TOHF), which integrates HVS (Human Visual System) for enhanced texture analysis. TOHF employs a two-stage thresholding strategy and dynamically adjusts feature point distribution, balancing computational efficiency and storage needs. We conducted experimental verification based on the ORB-SLAM3 framework on dataset from resource-limited device and the EuRoc dataset, focusing on matching rate, reprojection error, absolute trajectory error(ATE), and time efficiency. Results show that TOHF improves accuracy and robustness in vision-inertial navigation modes while maintaining real-time performance.
Recommended Citation
Li, Ruoqing; Zhao, Yaochi; Hu, Zhuhua; Qi, Wenlu; and Liu, Guangfeng
(2025)
"TOHF: A Feature Extractor for Resource-constrained Indoor VSLAM,"
Journal of System Simulation: Vol. 37:
Iss.
3, Article 12.
DOI: 10.16182/j.issn1004731x.joss.23-1334
Available at:
https://dc-china-simulation.researchcommons.org/journal/vol37/iss3/12
First Page
691
Last Page
703
CLC
TP391.9; TP212
Recommended Citation
Li Ruoqing, Zhao Yaochi, Hu Zhuhua, et al. TOHF: A Feature Extractor for Resource-constrained Indoor VSLAM[J]. Journal of System Simulation, 2025, 37(3): 691-703.
DOI
10.16182/j.issn1004731x.joss.23-1334
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