使用3D全身运动跟踪传感器的单手和双手手势的连续识别

P. Kristensson, Thomas Nicholson, A. Quigley
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引用次数: 65

摘要

本文提出了一种新的用于三维全身运动跟踪传感器(如Kinect)的无标记手势界面。我们的界面使用概率算法来增量预测用户的单手和双手手势,而他们仍然是清晰的。它支持对任意定义的手势模板进行实时缩放和平移不变识别。该界面支持两种方式的手势命令在稀薄的空气中显示在远处。首先,用户可以使用单手和双手手势直接发出命令。其次,用户可以使用他们的非惯用手来调整单手手势。我们的评估表明,该系统识别单手和双手手势的准确率为92.7%- 96.2%。
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Continuous recognition of one-handed and two-handed gestures using 3D full-body motion tracking sensors
In this paper we present a new bimanual markerless gesture interface for 3D full-body motion tracking sensors, such as the Kinect. Our interface uses a probabilistic algorithm to incrementally predict users' intended one-handed and twohanded gestures while they are still being articulated. It supports scale and translation invariant recognition of arbitrarily defined gesture templates in real-time. The interface supports two ways of gesturing commands in thin air to displays at a distance. First, users can use one-handed and two-handed gestures to directly issue commands. Second, users can use their non-dominant hand to modulate single-hand gestures. Our evaluation shows that the system recognizes one-handed and two-handed gestures with an accuracy of 92.7%--96.2%.
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