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  • 1.
    Chen, Jiandan
    et al.
    Blekinge Institute of Technology, School of Engineering, Department of Electrical Engineering.
    Khatibi, Siamak
    Blekinge Institute of Technology, School of Engineering, Department of Electrical Engineering.
    Kulesza, Wlodek
    Blekinge Institute of Technology, School of Engineering, Department of Electrical Engineering.
    Depth reconstruction uncertainty analysis and improvement: The dithering approach2010In: Image and Vision Computing, ISSN 0262-8856, E-ISSN 1872-8138, Vol. 29, no 9, p. 1377-1385Article in journal (Refereed)
    Abstract [en]

    The depth spatial quantization uncertainty is one of the factors which influence the depth reconstruction accuracy caused by a discrete sensor. This paper discusses the quantization uncertainty distribution, introduces a mathematical model of the uncertainty interval range, and analyzes the movements of the sensors in an Intelligent Vision Agent System. Such a system makes use of multiple sensors which control the deployment and autonomous servo of the system. This paper proposes a dithering algorithm which reduces the depth reconstruction uncertainty. The algorithm assures high accuracy from a few images taken by low-resolution sensors. The dither signal is estimated and then generated through an analysis of the iso-disparity planes. The signal allows for control of the camera movement. The proposed approach is validated and compared with a direct triangulation method. The simulation results are reported in terms of depth reconstruction error statistics. The physical experiment shows that the dithering method reduces the depth reconstruction error.

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