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Handling pure camera rotation in semi-dense monocular SLAM

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Abstract

In this paper, we present a method for semi-dense monocular simultaneous localization and mapping (SLAM) that is capable of dealing with pure camera rotation motion which brings forward a severe challenge for current direct (featureless) monocular SLAM approaches. A probabilistic depth map model built on Bayesian estimation is combined with the main framework of the state-of-the-art direct method LSD-SLAM. Using this model, both rotation-only and general camera motions could be tracked, and a consistent depth map could be built in real-time. Experimental results demonstrate the outstanding performance of the proposed system.

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Acknowledgements

This work is supported by the National 863 Program of China under Grant No. 2015AA016403 and the Natural Science Foundation of China under Grant Nos. 61472020, 61572061, 61602223.

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Authors and Affiliations

  1. State Key Laboratory of Virtual Reality Technology and Systems, Beihang University, Beijing, China

    Yao Zhou, Feihu Yan & Zhong Zhou

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  1. Yao Zhou
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  2. Feihu Yan
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  3. Zhong Zhou
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Correspondence to Feihu Yan.

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Zhou, Y., Yan, F. & Zhou, Z. Handling pure camera rotation in semi-dense monocular SLAM. Vis Comput 35, 123–132 (2019). https://doi.org/10.1007/s00371-017-1435-0

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  • DOI: https://doi.org/10.1007/s00371-017-1435-0

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