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An evaluation of 3D head pose estimation using the Microsoft Kinect v2

机译:使用Microsoft Kinect v2评估3D头部姿势估计

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The Kinect v2 sensor supports real-time non-invasive 3D head pose estimation. Because the sensor is small, widely available and relatively cheap it has great potential as a tool for groups interested in measuring head posture. In this paper we compare the Kinect's head pose estimates with a marker-based record of ground truth in order to establish its accuracy. During movement of the head and neck alone (with static torso), we find average errors in absolute yaw, pitch and roll angles of 2.0 +/- 1.2 degrees, 7.3 +/- 3.2 degrees and 2.6 +/- 0.7 degrees, and in rotations relative to the rest pose of 1.4 +/- 0.5 degrees, 2.1 +/- 0.4 degrees and 2.0 +/- 0.8 degrees. Larger head rotations where it becomes difficult to see facial features can cause estimation to fail (10.2 +/- 6.1% of all poses in our static torso range of motion tests) but we found no significant changes in performance with the participant standing further away from Kinect - additionally enabling full-body pose estimation - or without performing face shape calibration, something which is not always possible for younger or disabled participants. Where facial features remain visible, the sensor has applications in the non-invasive assessment of postural control, e.g. during a programme of physical therapy. In particular, a multi-Kinect setup covering the full range of head (and body) movement would appear to be a promising way forward. (C) 2016 Elsevier B.V. All rights reserved.
机译:Kinect v2传感器支持实时非侵入式3D头部姿势估计。由于该传感器体积小,可广泛使用并且相对便宜,因此它对于有兴趣测量头部姿势的人群具有巨大的潜力。在本文中,我们将Kinect的头部姿势估计值与基于标记的地面真实情况记录进行比较,以建立其准确性。在仅头部和颈部运动(带有静态躯干)期间,我们发现绝对偏航角,俯仰角和侧倾角分别为2.0 +/- 1.2度,7.3 +/- 3.2度和2.6 +/- 0.7度,并且在相对于静止姿势的旋转角度分别为1.4 +/- 0.5度,2.1 +/- 0.4度和2.0 +/- 0.8度。较大的头部旋转(很难看到面部特征)可能会导致估计失败(在我们的静态躯干运动测试范围内,所有姿势的占总姿势的10.2 +/- 6.1%),但是我们发现参与者的运动距离没有明显变化Kinect-还可以进行全身姿势估计-或不执行面部形状校准,这对于年幼或残疾的参与者而言并不总是可能的。在面部特征仍然可见的情况下,该传感器可用于姿势控制的非侵入性评估,例如:在物理治疗程序中。特别是,覆盖整个头部(和身体)运动范围的多Kinect设置似乎是一种有前途的方法。 (C)2016 Elsevier B.V.保留所有权利。

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