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Tennis video shot classification based on support vector machine

机译:基于支持向量机的网球视频镜头分类

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Video shot classification is one of the key technologies to achieve fast retrieval and browsing video. A novel approach of tennis shot classification based on SVM is proposed. After extracting sobel edge pixels ratios based on window as a classification feature, the optical flow measurements including foreground tracked points ratio (FPR) and mean length of motion vectors (MLV) are also calculated for classification. In the end, achieve the shot classification of tennis video by the way of support vector machine (SVM). Experiment shows that the method can better complete the shot classification of tennis video.
机译:视频镜头分类是实现视频快速检索和浏览的关键技术之一。提出了一种基于支持向量机的网球击球分类新方法。在基于窗口作为分类特征提取sobel边缘像素比率之后,还计算了包括前景跟踪点比率(FPR)和运动矢量平均长度(MLV)在内的光流测量结果以进行分类。最后,通过支持向量机(SVM)实现网球视频的镜头分类。实验表明,该方法可以较好地完成网球视频镜头的分类。

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