2021
DOI: 10.48550/arxiv.2102.13438
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Accurate Visual-Inertial SLAM by Feature Re-identification

Abstract: We propose a novel feature re-identification method for real-time visual-inertial SLAM. The front-end module of the state-of-the-art visual-inertial SLAM methods (e.g. visual feature extraction and matching schemes) relies on feature tracks across image frames, which are easily broken in challenging scenarios, resulting in insufficient visual measurement and accumulated error in pose estimation. In this paper, we propose an efficient drift-less SLAM method by reidentifying existing features from a spatial-temp… Show more

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