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
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;
Conference_Titel :
Industrial Electronics Society, IECON 2014 - 40th Annual Conference of the IEEE
DOI :
10.1109/IECON.2014.7048876