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Fusing Real-Time Depth Imaging with High Precision Pose Estimation by a Measurement Arm

机译:通过测量臂将实时深度成像与高精度姿势估计融合在一起

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Recently, depth cameras have emerged which capture dense depth images in real-time. To benefit from their 3D imaging capabilities in interactive applications which support an arbitrary camera movement, the position and orientation of the depth camera needs to be robustly estimated in real time for each captured depth image. Therefore, this paper describes how to combine a depth camera with a mechanical measurement arm to fuse real-time depth imaging with real-time, high precision pose estimation. Estimating the pose of a depth camera with a measurement arm has three major advantages over 2D/3D image based optical pose estimation: The measurement arm has a very precise guaranteed accuracy better than 0.1mm, the pose estimation accuracy is not influenced by the captured scene and the computational load is much lower than for optical pose estimation, leaving more processing power for the applications themselves.
机译:近来,出现了深度相机,其实时捕获密集的深度图像。为了在支持任意相机移动的交互式应用程序中受益于其3D成像功能,需要针对每个捕获的深度图像实时可靠地估计深度相机的位置和方向。因此,本文描述了如何将深度相机与机械测量臂结合在一起,以融合实时深度成像与实时,高精度姿态估计。与基于2D / 3D图像的光学姿态估计相比,估计具有测量臂的深度相机的姿态具有三个主要优点:测量臂具有非常精确的保证精度,优于0.1mm,姿态估计精度不受捕获的场景的影响而且计算量比光学姿态估计要低得多,为应用程序本身留下了更多的处理能力。

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