Efficient colorization of large-scale point cloud using multi-pass Z-ordering

Sunyoung Cho, Jizhou Yan, Yasuyuki Matsushita, Hyeran Byun

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    3 Citations (Scopus)

    Abstract

    We present an efficient colorization method for a large scale point cloud using multi-view images. To address the practical issues of noisy camera parameters and color inconsistencies across multi-view images, our method takes an optimization approach for achieving visually pleasing point cloud colorization. We introduce a multi-pass Zordering technique that efficiently defines a graph structure to a large-scale and un-ordered set of 3D points, and use the graph structure for optimizing the point colors to be assigned. Our technique is useful for defining minimal but sufficient connectivities among 3D points so that the optimization can exploit the sparsity for efficiently solving the problem. We demonstrate the effectiveness of our method using synthetic datasets and a large-scale real-world data in comparison with other graph construction techniques.

    Original languageEnglish
    Title of host publicationProceedings - 2014 International Conference on 3D Vision, 3DV 2014
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    Pages689-696
    Number of pages8
    ISBN (Electronic)9781479970018
    DOIs
    Publication statusPublished - 2015 Feb 6
    Event2014 2nd International Conference on 3D Vision, 3DV 2014 - Tokyo, Japan
    Duration: 2014 Dec 82014 Dec 11

    Publication series

    NameProceedings - 2014 International Conference on 3D Vision, 3DV 2014

    Other

    Other2014 2nd International Conference on 3D Vision, 3DV 2014
    Country/TerritoryJapan
    CityTokyo
    Period14/12/814/12/11

    All Science Journal Classification (ASJC) codes

    • Computer Vision and Pattern Recognition
    • Computer Science Applications

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