KUKU

KU ScholarWorks

  • myKU
  • Email
  • Enroll & Pay
  • KU Directory
    • Login
    View Item 
    •   KU ScholarWorks
    • Engineering
    • Electrical Engineering and Computer Science Scholarly Works
    • View Item
    •   KU ScholarWorks
    • Engineering
    • Electrical Engineering and Computer Science Scholarly Works
    • View Item
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Robust Structure and Motion Recovery Based on Augmented Factorization

    Thumbnail
    View/Open
    Wang_2017.pdf (2.611Mb)
    Issue Date
    2017-09-21
    Author
    Wang, Guanghui
    Publisher
    Institute of Electrical and Electronics Engineers
    Type
    Article
    Article Version
    Scholarly/refereed, publisher version
    Rights
    © 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.
    Metadata
    Show full item record
    Abstract
    This paper proposes a new strategy to promote the robustness of structure from motion algorithm from uncalibrated video sequences. First, an augmented affine factorization algorithm is formulated to circumvent the difficulty in image registration with noise and outliers contaminated data. Then, an alternative weighted factorization scheme is designed to handle the missing data and measurement uncertainties in the tracking matrix. Finally, a robust strategy for structure and motion recovery is proposed to deal with outliers and large measurement noise. This paper makes the following main contributions: 1) An augmented factorization algorithm is proposed to circumvent the difficult image registration problem of previous affine factorization, and the approach is applicable to both rigid and nonrigid scenarios; 2) by employing the fact that image reprojection residuals are largely proportional to the error magnitude in the tracking data, a simple outliers detection approach is proposed; and 3) a robust factorization strategy is developed based on the distribution of the reprojection residuals. Furthermore, the proposed approach can be easily extended to nonrigid scenarios. Experiments using synthetic and real image data demonstrate the robustness and efficiency of the proposed approach over previous algorithms.
    URI
    http://hdl.handle.net/1808/27389
    DOI
    https://doi.org/10.1109/ACCESS.2017.2755019
    Collections
    • Electrical Engineering and Computer Science Scholarly Works [288]
    Citation
    G. Wang, "Robust Structure and Motion Recovery Based on Augmented Factorization," in IEEE Access, vol. 5, pp. 18999-19011, 2017. doi: 10.1109/ACCESS.2017.2755019

    Items in KU ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.


    We want to hear from you! Please share your stories about how Open Access to this item benefits YOU.


    Contact KU ScholarWorks
    785-864-8983
    KU Libraries
    1425 Jayhawk Blvd
    Lawrence, KS 66045
    785-864-8983

    KU Libraries
    1425 Jayhawk Blvd
    Lawrence, KS 66045
    Image Credits
     

     

    Browse

    All of KU ScholarWorksCommunities & CollectionsThis Collection

    My Account

    LoginRegister

    Statistics

    View Usage Statistics

    Contact KU ScholarWorks
    785-864-8983
    KU Libraries
    1425 Jayhawk Blvd
    Lawrence, KS 66045
    785-864-8983

    KU Libraries
    1425 Jayhawk Blvd
    Lawrence, KS 66045
    Image Credits
     

     

    The University of Kansas
      Contact KU ScholarWorks
    Lawrence, KS | Maps
     
    • Academics
    • Admission
    • Alumni
    • Athletics
    • Campuses
    • Giving
    • Jobs

    The University of Kansas prohibits discrimination on the basis of race, color, ethnicity, religion, sex, national origin, age, ancestry, disability, status as a veteran, sexual orientation, marital status, parental status, gender identity, gender expression and genetic information in the University’s programs and activities. The following person has been designated to handle inquiries regarding the non-discrimination policies: Director of the Office of Institutional Opportunity and Access, IOA@ku.edu, 1246 W. Campus Road, Room 153A, Lawrence, KS, 66045, (785)864-6414, 711 TTY.

     Contact KU
    Lawrence, KS | Maps