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ViPR: Visual-Odometry-aided Pose Regression for 6DoF Camera Localization [article]

Felix Ott, Tobias Feigl, Christoffer Löffler, Christopher Mutschler
2019 arXiv   pre-print

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https://web.archive.org/web/20200321020555/https://arxiv.org/pdf/1912.08263v2.pdf

A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL. The file type is application/pdf.

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2020 accepted
doi:10.1109/cvprw50498.2020.00029 arXiv:1912.08263v3 fatcat:kwdctl7a4ffkdlubc5cf3ebojy
2019 pre-print
arXiv:1912.08263v1 fatcat:spkepeqb25d6nnaoedxar6ipeu
We propose ViPR, a novel architecture for long-term 6DoF VO that leverages synergies between absolute pose estimates (from PoseNet-like architectures) and relative pose estimates (from FlowNet-based architectures  ...  Visual Odometry (VO) accumulates a positional drift in long-term robot navigation tasks.  ...  Acknowledgements This work was supported by the Bavarian Ministry for Economic Affairs, Infrastructure, Transport and Technology through the Center for Analytics-Data-Applications (ADA-Center) within the  ... 
arXiv:1912.08263v2 fatcat:soynuvfnwbgkxcnihwiw5rcz5u
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Citation

Felix Ott, Tobias Feigl, Christoffer Löffler, Christopher Mutschler. "ViPR: Visual-Odometry-aided Pose Regression for 6DoF Camera Localization." arXiv (2019)