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首页> 外文期刊>Electronics Letters >Direct three-dimensional head pose estimation from Kinect-type sensors
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Direct three-dimensional head pose estimation from Kinect-type sensors

机译:Kinect型传感器的直接三维头部姿势估计

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摘要

A direct method for recovering three-dimensional (3D) head motion parameters from a sequence of range images acquired by Kinect sensors is presented. Based on the range images, a new version of the optical flow constraint equation is derived, which can be used to directly estimate 3D motion parameters without any need of imposing other constraints. Since all calculations with the new constraint equation are based on the range images, Z(x, y, t), the existing techniques and experiences developed and accumulated on the topic of motion from optical flow can be directly applied simply by treating the range images as normal intensity images I(x, y, t). In this reported work, it is demonstrated how to employ the new optical flow constraint equation to recover the 3D motion of a moving head from the sequences of range images, and furthermore, how to use an old trick to handle the case when the optical flow is large. It is shown, in the end, that the performance of the proposed approach is comparable with that of some of the state-of-the-art approaches that use range data to recover 3D motion parameters.
机译:提出了一种直接方法,用于从Kinect传感器获取的一系列距离图像中恢复三维(3D)头部运动参数。基于距离图像,可以导出光流约束方程的新版本,该方程可用于直接估算3D运动参数,而无需施加其他约束。由于使用新的约束方程式进行的所有计算均基于距离图像Z(x,y,t),因此通过处理距离图像可以直接应用从光流运动领域积累的现有技术和经验作为正常强度图像I(x,y,t)。在这份报告的工作中,演示了如何使用新的光流约束方程式从距离图像序列中恢复移动头的3D运动,此外,如何使用旧技巧来处理光流时的情况。大。最终表明,所提出的方法的性能与某些使用范围数据恢复3D运动参数的最新方法的性能相当。

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    《Electronics Letters》 |2014年第4期|268-270|共3页
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