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Dynamic Gesture Capture, Location and Tracking Based on MeanShift Algorithm

机译:基于MeanShift算法的动态手势捕获,定位与跟踪

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In this paper, dynamic gesture capture and tracking based on MeanShift algorithm for human-computer interaction system is proposed. In this method, the rectangular box representing the hand position is used as the control signal input and the initial detection target tracking. Thus the dynamic gesture video is effectively processed. In this paper, Python3 OpenCV library is adopted as the main processing library for experimental analysis. The initial capture and positioning of hand position and subsequent tracking experiments are carried out on a video of hand movement. Through the comparison and analysis with Camshift algorithm, the experimental results show that MeanShift algorithm achieves a good dynamic tracking effect of gesture position.
机译:本文提出了一种基于MeanShift算法的人机交互系统动态手势捕获与跟踪方法。在这种方法中,代表手位置的矩形框用作控制信号输入和初始检测目标跟踪。因此,有效地处理了动态手势视频。本文采用Python3 OpenCV库作为实验分析的主要处理库。在手部运动的视频上进行手部位置的初始捕获和定位以及随后的跟踪实验。通过与Camshift算法的比较分析,实验结果表明,MeanShift算法取得了较好的手势位置动态跟踪效果。

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