TOHF:一种针对资源受限室内VSLAM的特征提取器  

TOHF:A Feature Extractor for Resource-constrained Indoor VSLAM

作　　者：李若晴 赵瑶池[1] 胡祝华[1] 戚文璐 刘广丰 Li Ruoqing;Zhao Yaochi;Hu Zhuhua;Qi Wenlu;Liu Guangfeng(School of Cyberspce Security,Hainan University,Haikou 570228,China;School of Information and Communication Engineering Hainan University,Haikou 570228,China)

机构地区：[1]海南大学网络空间安全学院,海南海口570228 [2]海南大学信息与通信工程学院,海南海口570228

出　　处：《系统仿真学报》2025年第3期691-703,共13页Journal of System Simulation

基　　金：国家自然科学基金(62161010);海南省自然科学基金(623RC446);海南省种业实验室资助项目(B23H10004);海南省重点研发计划(ZDYF2022GXJS348和ZDYF2022SHFZ039)。

摘　　要：为解决现有VSLAM特征提取器在室内环境中对纹理和光照变化敏感、特征点冗余导致的局部依赖性过强以及硬件资源受限时的存储开销问题,提出了一种面向纹理的均匀FAST特征提取器(texture-oriented and homogenized FAST feature extractor, TOHF)。结合HVS(human visual system),采用二阶段阈值策略来更敏感地应对纹理的清晰度和复杂度差异。根据特征点密度的变化来动态调整特征点的分布,在兼顾计算效率和存储开销的同时,保证特征点分布结构信息。在资源受限设备录制的数据集和官方Eu Roc数据集上基于ORB-SLAM3框架开展实验,采用匹配率、重投影误差、绝对轨迹误差(ATE)和耗时作为评估指标。实验结果表明:TOHF在视觉加惯导模式下带来更高精度和鲁棒性的同时,仍满足实时性要求。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.

关 键 词：VSLAM HVS 特征提取 ORB-SLAM3 纹理 

分 类 号：TP391.9[自动化与计算机技术—计算机应用技术] TP212[自动化与计算机技术—计算机科学与技术]