• DocumentCode
    1796314
  • Title

    Performance Evaluation of 3D Local Surface Descriptors for Low and High Resolution Range Image Registration

  • Author

    Ali Shah, S. Aamir ; Bennamoun, Mohammed ; Boussaid, Farid

  • Author_Institution
    Sch. of Comput. Sci. & Software Eng., Univ. of Western Australia, Crawley, WA, Australia
  • fYear
    2014
  • fDate
    25-27 Nov. 2014
  • Firstpage
    1
  • Lastpage
    7
  • Abstract
    Despite the advent and popularity of low-cost commercial sensors (e.g., Microsoft Kinect), research in 3D vision still primarily focuses on the development of advanced algorithms geared towards high resolution data. This paper presents a comparative performance evaluation of renowned state-of-the-art 3D local surface descriptors for the task of registration of both high and low resolution range image data. The datasets used in these experiments are the renowned high resolution Stanford 3D models dataset and challenging low resolution Washington RGB-D object dataset. Experimental results show that the performance of certain local surface descriptors is significantly affected by low resolution data.
  • Keywords
    computer vision; image colour analysis; image registration; image resolution; image sensors; 3D local surface descriptors; 3D vision; high resolution Stanford 3D models; high resolution range image registration; low resolution Washington RGB-D object dataset; low resolution range image registration; low-cost commercial sensors; performance evaluation; Accuracy; Image resolution; Kernel; Niobium; Robustness; Three-dimensional displays; Vectors;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Digital lmage Computing: Techniques and Applications (DlCTA), 2014 International Conference on
  • Conference_Location
    Wollongong, NSW
  • Type

    conf

  • DOI
    10.1109/DICTA.2014.7008123
  • Filename
    7008123