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Statistical Analysis-Based Error Models for the Microsoft Kinect™ Depth Sensor

机译:Microsoft Kinect ™深度传感器的基于统计分析的错误模型

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The stochastic error characteristics of the Kinect sensing device are presented for each axis direction. Depth (z) directional error is measured using a flat surface, and horizontal (x) and vertical (y) errors are measured using a novel 3D checkerboard. Results show that the stochastic nature of the Kinect measurement error is affected mostly by the depth at which the object being sensed is located, though radial factors must be considered, as well. Measurement and statistics-based models are presented for the stochastic error in each axis direction, which are based on the location and depth value of empirical data measured for each pixel across the entire field of view. The resulting models are compared against existing Kinect error models, and through these comparisons, the proposed model is shown to be a more sophisticated and precise characterization of the Kinect error distributions.
机译:Kinect传感设备的随机误差特性在每个轴方向上都有显示。使用平面测量深度(z)方向误差,使用新型3D棋盘测量水平(x)和垂直(y)误差。结果表明,尽管必须考虑径向因素,但Kinect测量误差的随机性主要受被检测物体所在深度的影响。提出了针对每个轴方向上的随机误差的基于测量和统计的模型,这些模型基于在整个视场中为每个像素测量的经验数据的位置和深度值。将所得的模型与现有的Kinect误差模型进行比较,并且通过这些比较,所提出的模型显示出对Kinect误差分布的更复杂和精确的表征。

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