• DocumentCode
    3566382
  • Title

    Statistical models of horizontal and vertical stochastic noise for the Microsoft Kinect™ sensor

  • Author

    Choo, Benjamin ; DeVore, Michael D. ; Beling, Peter A.

  • Author_Institution
    Dept. of Syst. & Inf. Eng., Univ. of Virginia, Charlottesville, VA, USA
  • fYear
    2014
  • Firstpage
    2624
  • Lastpage
    2630
  • Abstract
    Noise characteristics for the Microsoft Kinect sensor are presented. Horizontal (x) and vertical (y) stochastic noise are measured using a novel 3D checker board. Results show that the noise is affected mostly by the depth at which the object is sensed and by the radial distance from the center of the field of view. Measurement-based models for the noise in horizontal and vertical axes are presented. The proposed model is compared against existing models in literature and shows better results by considering the horizontal and vertical location of the depth measurement.
  • Keywords
    sensors; stochastic processes; 3D checker board; Microsoft Kinect sensor; depth measurement; field of view; horizontal stochastic noise; measurement-based models; noise characteristics; radial distance; statistical models; vertical stochastic noise; Image edge detection; Mathematical model; Noise; Noise measurement; Robot sensing systems; Stochastic processes; Three-dimensional displays; Microsoft Kinect™; callibration; statistical model; stochastic noise;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Industrial Electronics Society, IECON 2014 - 40th Annual Conference of the IEEE
  • Type

    conf

  • DOI
    10.1109/IECON.2014.7048876
  • Filename
    7048876