BRADFORD SCHOLARS

    • Sign in
    View Item 
    •   Bradford Scholars
    • Engineering and Informatics
    • Engineering and Informatics Publications
    • View Item
    •   Bradford Scholars
    • Engineering and Informatics
    • Engineering and Informatics Publications
    • View Item
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Browse

    All of Bradford ScholarsCommunitiesAuthorsTitlesSubjectsPublication DateThis CollectionAuthorsTitlesSubjectsPublication Date

    My Account

    Sign in

    HELP

    Bradford Scholars FAQsCopyright Fact SheetPolicies Fact SheetDeposit Terms and ConditionsDigital Preservation Policy

    Statistics

    Most Popular ItemsStatistics by CountryMost Popular Authors

    Object registration in semi-cluttered and partial-occluded scenes for augmented reality

    • CSV
    • RefMan
    • EndNote
    • BibTex
    • RefWorks
    Thumbnail
    View/Open
    Final published version.pdf (4.059Mb)
    Download
    Publication date
    2018-06
    Author
    Gao, Q.H.
    Wan, Tao Ruan
    Tang, W.
    Chen, L.
    Keyword
    Augmented reality
    3D object recognition and matching
    3D point clouds
    SLAM algorithm
    Rights
    © The Author(s) 2018 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
    Peer-Reviewed
    Yes
    
    Metadata
    Show full item record
    Abstract
    This paper proposes a stable and accurate object registration pipeline for markerless augmented reality applications. We present two novel algorithms for object recognition and matching to improve the registration accuracy from model to scene transformation via point cloud fusion. Whilst the first algorithm effectively deals with simple scenes with few object occlusions, the second algorithm handles cluttered scenes with partial occlusions for robust real-time object recognition and matching. The computational framework includes a locally supported Gaussian weight function to enable repeatable detection of 3D descriptors. We apply a bilateral filtering and outlier removal to preserve edges of point cloud and remove some interference points in order to increase matching accuracy. Extensive experiments have been carried to compare the proposed algorithms with four most used methods. Results show improved performance of the algorithms in terms of computational speed, camera tracking and object matching errors in semi-cluttered and partial-occluded scenes.
    URI
    http://hdl.handle.net/10454/16671
    Version
    Published version
    Citation
    Gao QH, Wan TR, Tang W, et al (2018) Object registration in semi-cluttered and partial-occluded scenes for augmented reality. Multimedia Tools and Applications. 78(11): 15079-15099.
    Link to publisher’s version
    https://doi.org/10.1007/s11042-018-6905-5
    Type
    Article
    Collections
    Engineering and Informatics Publications

    entitlement

     
    DSpace software (copyright © 2002 - 2023)  DuraSpace
    Quick Guide | Contact Us
    Open Repository is a service operated by 
    Atmire NV
     

    Export search results

    The export option will allow you to export the current search results of the entered query to a file. Different formats are available for download. To export the items, click on the button corresponding with the preferred download format.

    By default, clicking on the export buttons will result in a download of the allowed maximum amount of items.

    To select a subset of the search results, click "Selective Export" button and make a selection of the items you want to export. The amount of items that can be exported at once is similarly restricted as the full export.

    After making a selection, click one of the export format buttons. The amount of items that will be exported is indicated in the bubble next to export format.