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Simulating Kinect Infrared and Depth Images.

Michael J Landau, Benjamin Y Choo, Peter A Beling

    IEEE Transactions on Cybernetics
    |November 20, 2015
    PubMed
    Summary
    This summary is machine-generated.

    This study introduces a new simulator for Microsoft Kinect sensors, modeling infrared (IR) and depth image errors. The simulator accurately predicts depth errors, aiding in the development of more reliable Kinect applications.

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    Area of Science:

    • Computer Vision
    • Robotics
    • Sensor Technology

    Background:

    • Microsoft Kinect sensors are widely used in research, but existing error models neglect infrared (IR) image contributions.
    • Accurate error modeling is crucial for developing new Kinect applications and requires robust datasets.

    Purpose of the Study:

    • To propose a high-fidelity simulator for predicting Kinect infrared (IR) and depth images.
    • To model the physical processes and error sources affecting Kinect depth estimation.

    Main Methods:

    • Developed a simulator incorporating Kinect's physics, IR dot pattern, and disparity processing.
    • Modeled systematic errors like depth shadowing and stochastic noise including IR speckle.
    • Incorporated correlation-based disparity estimation and subpixel refinement.

    Main Results:

    • The simulator accurately predicts axial depth error for tilted flat surfaces.
    • It also accurately models bias and standard lateral error at object edges.
    • The model accounts for Kinect's stereo triangulation characteristics.

    Conclusions:

    • The proposed simulator provides a more accurate representation of Kinect sensor errors.
    • This tool can enhance the development and testing of new Kinect-based systems.
    • Understanding and modeling IR image contributions is key to improving depth accuracy.