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Automatic alignment and completion of point cloud environments using XR data

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Published:25 July 2022Publication History

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References

  1. Dimitrios Bolkas, Jeffrey Chiampi, John Chapman, and Vincent F. Pavill. 2020. Creating a virtual reality environment with a fusion of sUAS and TLS point-clouds. International Journal of Image and Data Fusion 11, 2 (2020), 136–161. https://doi.org/10.1080/19479832.2020.1716861Google ScholarGoogle ScholarCross RefCross Ref
  2. E. Lachat, T. Landes, and P. Grussenmeyer. 2016. Combination of TLS point clouds and 3D data from kinect V2 sensor to complete indoor models. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives 41 (2016), 659–666. https://doi.org/10.5194/isprsarchives-XLI-B5-659-2016Google ScholarGoogle Scholar
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  4. T. Partovi, M. Dähne, M. Maboudi, D. Krueger, and M. Gerke. 2021. Automatic integration of laser scanning and photogrammetric point clouds: From acquisition to co-registration. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives 43, B1-2021 (2021), 85–92. https://doi.org/10.5194/isprs-archives-XLIII-B1-2021-85-2021Google ScholarGoogle Scholar
  5. Qian Yi Zhou, Jaesik Park, and Vladlen Koltun. 2016. Fast global registration. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 9906 LNCS, August(2016), 766–782. https://doi.org/10.1007/978-3-319-46475-6_47Google ScholarGoogle Scholar

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  • Published in

    cover image ACM Conferences
    SIGGRAPH '22: ACM SIGGRAPH 2022 Posters
    July 2022
    132 pages
    ISBN:9781450393614
    DOI:10.1145/3532719

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    Publication History

    • Published: 25 July 2022

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