RD-VIO : Robust Visual-Inertial Odometry for Mobile Augmented Reality in Dynamic Environments
It is typically challenging for visual or visual-inertial odometry systems to handle the problems of dynamic scenes and pure rotation. In this work, we design a novel visual-inertial odometry (VIO) system called RD-VIO to handle both of these two problems. First, we propose an IMU-PARSAC algorithm w...
Publié dans: | IEEE transactions on visualization and computer graphics. - 1996. - 30(2024), 10 vom: 12. Okt., Seite 6941-6955 |
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Auteur principal: | |
Autres auteurs: | , , , , , |
Format: | Article en ligne |
Langue: | English |
Publié: |
2024
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Accès à la collection: | IEEE transactions on visualization and computer graphics |
Sujets: | Journal Article |
Résumé: | It is typically challenging for visual or visual-inertial odometry systems to handle the problems of dynamic scenes and pure rotation. In this work, we design a novel visual-inertial odometry (VIO) system called RD-VIO to handle both of these two problems. First, we propose an IMU-PARSAC algorithm which can robustly detect and match keypoints in a two-stage process. In the first state, landmarks are matched with new keypoints using visual and IMU measurements. We collect statistical information from the matching and then guide the intra-keypoint matching in the second stage. Second, to handle the problem of pure rotation, we detect the motion type and adapt the deferred-triangulation technique during the data-association process. We make the pure-rotational frames into the special subframes. When solving the visual-inertial bundle adjustment, they provide additional constraints to the pure-rotational motion. We evaluate the proposed VIO system on public datasets and online comparison. Experiments show the proposed RD-VIO has obvious advantages over other methods in dynamic environments |
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Description: | Date Revised 05.09.2024 published: Print-Electronic Citation Status PubMed-not-MEDLINE |
ISSN: | 1941-0506 |
DOI: | 10.1109/TVCG.2024.3353263 |