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The athletes' irrational posture recognition based on minimizing image sequences

机译:基于最小图像序列的运动员的非理性姿态识别

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The paper proposes a kind of athletes' irrational postures recognition technology based on minimizing image sequences by analyzing the shape bases of the collected images and estimating the overall movement parameters in the single-frame movement images. The irrational movement features information will be projected in the gray fields to obtain the embedded hidden information in the overall movement posture images to achieve the recognition of irrational postures. The experimental results illustrate the posture correction offsets by the proposed improved algorithm are smaller than those in traditional methods with high correction accuracy and the signal to noise ratios of the peaks are increased. The results show the superiority of the algorithm which can be well applied in the motion image fusion and identification areas.
机译:本文提出了一种基于最小化图像序列来提出一种运动员的非理性姿势识别技术,通过分析收集的图像的形状基础并估计单帧移动图像中的整体运动参数。非理性运动功能信息将投影在灰色字段中,以获得整体运动姿势图像中的嵌入式隐藏信息,以实现对非理性姿势的识别。实验结果说明了所提出的改进算法的姿势校正偏移小于具有高校正精度的传统方法的校正偏移,并且增加了峰值的信噪比。结果表明,在运动图像融合和识别区域中可以很好地应用的算法的优越性。

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