• DocumentCode
    3095797
  • Title

    Multi-view point clouds registration and stitching based on SIFT feature

  • Author

    Chu, Jun ; Nie, Chun-mei

  • Author_Institution
    Inst. of Comput. Vision, Nanchang Hang kong Univ., Nanchang, China
  • Volume
    1
  • fYear
    2011
  • fDate
    11-13 March 2011
  • Firstpage
    274
  • Lastpage
    278
  • Abstract
    In order to solve multi-view point clouds registration in large non-feature marked scenes, a new registration and stitching method was proposed based on 2D SIFT(Scale-invariant feature transform) features. Firstly, we used texture mapping method to generate 2D effective texture image, and then extracted and match SIFT features, obtained accurate key points and registration relationship between the effective texture images. Secondly, we reflected the SIFT key points and registration relationship to the 3D point clouds data, obtained key points and registration relationship of multi-view point clouds, we can achieve multi-view point clouds stitching. Our algorithm used texture mapping method to generate 2D effective texture image, it can eliminate interference of the holes and ineffective points, and can eliminate unnecessary mistake matching. Our algorithm used correct extracted matching point pairs to stitch, avoiding stepwise iterated of ICP algorithm, so our algorithm is simple to calculate, and it´s matching precision and matching efficiency are improved to some extent. We carried experiments on two-view point clouds in two large indoor; the experiment results verified the validity of our algorithm.
  • Keywords
    feature extraction; image matching; image registration; image texture; 2D SIFT; 2D effective texture images; ICP algorithm; Scale Invariant feature transform; feature extraction; matching point pairs; multiview point clouds registration; multiview point clouds stitching; texture mapping method; Algorithm design and analysis; Equations; Feature extraction; Filling; Iterative closest point algorithm; Mathematical model; Three dimensional displays; Multi-view point clouds registration; SIFT key point; multi-view point clouds stitching; texture mapping;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Research and Development (ICCRD), 2011 3rd International Conference on
  • Conference_Location
    Shanghai
  • Print_ISBN
    978-1-61284-839-6
  • Type

    conf

  • DOI
    10.1109/ICCRD.2011.5764019
  • Filename
    5764019