Fusing structure from motion and simulation-augmented pose regression from optical flow for challenging indoor environments
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Published:2024-08
Issue:
Volume:103
Page:104256
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ISSN:1047-3203
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Container-title:Journal of Visual Communication and Image Representation
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language:en
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Short-container-title:Journal of Visual Communication and Image Representation
Author:
Ott FelixORCID,
Heublein LucasORCID,
Rügamer DavidORCID,
Bischl BerndORCID,
Mutschler ChristopherORCID
Reference112 articles.
1. VLocNet＋＋: Deep multitask learning for semantic visual localization and odometry;Radwan;IEEE Robot. Autom. Lett.,2018
2. C. Löffler, S. Riechel, J. Fischer, C. Mutschler, Evaluation Criteria for Inside-Out Indoor Positioning Systems Based on Machine Learning, in: IEEE Intl. Conf. on Indoor Positioning and Indoor Navigation, IPIN, Nantes, France, 2018, pp. 1–8, http://dx.doi.org/10.1109/IPIN.2018.8533862.
3. Estimating TOA reliability with variational autoencoders;Stahlke;IEEE Sens. J.,2022
4. End-to-end learning framework for IMU-based 6-DOF odometry;do Monte Lima;MDPI Sensors,2019
5. A. Kendall, M. Grimes, R. Cipolla, PoseNet: A Convolutional Network for Real-Time 6-DOF Camera Relocalization, in: Proc. of the IEEE/CVF Intl. Conf. on Computer Vision, ICCV, Santiago de Chile, Chile, 2015, pp. 2938–2946, http://dx.doi.org/10.1109/ICCV.2015.336.