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Dynamic gesture recognition algorithm in human computer interaction

机译:人机交互中的动态手势识别算法

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Human computer interaction (HCI) is a classic topic, and hand gesture is one of the most natural languages, so the key point in human computer interaction is hand gesture recognition. A skin color model based on Hue is utilized to detect skin color regions like hands. To distinguish the face and hand, a simple and fast hand segmentation algorithm is developed. Moreover, we use the least square method to fit the trajectory of hand gravity motion and the angle and direction of the movement is got by the inverse trigonometric function of the slope of the fitted line. Ten people doing 80 hand gestures in low and high illumination environment are tested. Experimental results show that the accuracy is 94.375% in average and the processing time is 34ms per frame. These demonstrated the good real-time and robustness of the proposed approach.
机译:人机交互(HCI)是一个经典主题,手势是最自然的语言之一,因此,人机交互的关键是手势识别。利用基于色相的肤色模型来检测诸如手的肤色区域。为了区分面部和手部,开发了一种简单快速的手部分割算法。此外,我们使用最小二乘法拟合手部重力运动的轨迹,并通过拟合线的斜率的反三角函数获得运动的角度和方向。测试了十个人在低光照和高光照环境下做80个手势的能力。实验结果表明,平均精度为94.375%,每帧处理时间为34ms。这些证明了所提出方法的良好的实时性和鲁棒性。

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