研究目的
To present a method for modeling the intrinsic and extrinsic parameters of the infrared and colour cameras, and more importantly the distortions in the depth image of the Kinect system, aiming to improve the geometric accuracy and reduce systematic depth discontinuities.
研究成果
The presented self-calibration method significantly improves the geometric accuracy and reduces systematic depth discontinuities in the Kinect system. Future work will explore the stability of calibration parameters and the inclusion of additional features to enhance precision.
研究不足
The study is limited to the calibration of the Kinect system using a planar target field, which may not fully represent 3D volumes. The method assumes rigid mounting of the optical sensors, and the stability of calibration parameters over time is not addressed.
1：Experimental Design and Method Selection:
The study employs a photogrammetric bundle adjustment with self-calibration model to correct systematic errors in the Kinect system. The methodology includes modeling the intrinsic and extrinsic parameters of the infrared and colour cameras, and distortions in the depth image.
2：Sample Selection and Data Sources:
Two Kinect for Xbox sensors were used, with images captured using the standard VGA resolution. A planar target with signalized targets was observed from various poses.
3：List of Experimental Equipment and Materials:
Microsoft Kinect sensors, a planar checkerboard target, and software tools including the MATLAB Camera Calibration Toolbox and the Microsoft Kinect SDK.
4：Experimental Procedures and Operational Workflow:
Following a warm-up period, depth, IR, and RGB images of a checkerboard target were acquired from various positions and orientations. The images were processed to measure corners and depth values, followed by bundle adjustment with self-calibration.
5：Data Analysis Methods:
The data were analyzed using least-squares optimization, variance component estimation, and Baarda’s data snooping to minimize outliers.
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