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Feature Extraction from 2D Gesture Trajectory in Dynamic Hand Gesture Recognition

机译:动态手势识别中的2D手势轨迹特征提取

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Vision-based hand gesture recognition is a popular research topic for human-machine interaction (HMI). We have earlier developed a model-based method for tracking hand motion in complex scene by using Hausdorff tracker. In this paper, we now propose to extract certain features from the gesture trajectory so as to identify the form of the trajectory. Thus, these features can be efficiently used for trajectory guided recognition/classification of hand gestures. Our experimental results show 95% of accuracy in identifying the forms of the gesture trajectories. This indicates that the trajectory features proposed in this paper are appropriate for defining a particular gesture trajectory.
机译:基于视觉的手势识别是人机交互(HMI)的流行研究主题。我们早先通过使用Hausdorff跟踪器在复杂场景中跟踪基于模型的方法。在本文中,我们现在建议从手势轨迹中提取某些特征,以便识别轨迹的形式。因此,这些特征可以有效地用于手势的轨迹引导识别/分类。我们的实验结果显示了识别姿态轨迹的形式的95%的准确性。这表明本文提出的轨迹特征适用于定义特定的手势轨迹。

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