Multi-level Pixel Detection Algorithm Based on Monocular Visualinertial System

Konferenz: ISCTT 2021 - 6th International Conference on Information Science, Computer Technology and Transportation
26.11.2021 - 28.11.2021 in Xishuangbanna, China

Tagungsband: ISCTT 2021

Seiten: 5Sprache: EnglischTyp: PDF

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Yao, Xinling; Zhao, Junyang; Zhou, Zhaofa; Guan, Shiyin (Xi’an Research Institute of Hi-Tech, Gaoxin, Xi’an, Shaanxi, China)

To enhance the localization accuracy of the conventional monocular visual-inertial localization system, a multi-level pixel feature detection algorithm combining pixel-level and sub-pixel-level is proposed. The feature detection firstly performs initial feature detection by pixel-level feature algorithm to obtain the number of feature points to be optimized, then iterates the initial values by sub-pixel detection algorithm to improve the extraction accuracy of the corner, and finally applies edge constraints to the results to prevent the detection of sub-pixel corner edge from crossing the boundary. According to the comparison experiments on the EuRoC dataset, the algorithm improves the accuracy of system localization compared to the VINS-mono algorithm.