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The tracking study of 3D image feature points of aerobic movements of high difficulty

机译:高难度有氧运动3D图像特征点的跟踪研究

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Tracking the 3D image feature points of aerobic movements of high difficulty can improve the quality of aerobic movements. The current method takes the windowed area as the tracking template to complete the track of feature points with low efficiency. For that reason, a method based on Gabor is presented with which to track the 3D image feature points of aerobic movements of high difficulty. The method extracts feature points with SIFT algorithms, classifies feature points according to AdaBoost algorithms, and tracks feature points through the image pyramid. The experiment shows that the mentioned method enhances the accuracy of tracking the 3D image feature points of aerobic movements.
机译:跟踪高难度有氧运动的3D图像特征点可以提高有氧运动的质量。当前的方法以窗口区域为跟踪模板,以低效率完成特征点的跟踪。因此,提出了一种基于Gabor的方法,该方法可以跟踪高难度有氧运动的3D图像特征点。该方法使用SIFT算法提取特征点,根据AdaBoost算法对特征点进行分类,并通过图像金字塔跟踪特征点。实验表明,所提方法提高了有氧运动3D图像特征点的跟踪精度。

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