中文摘要：

基于内容的体育视频分类是高效管理大量体育视频数据的关键步骤之一，为提高体育视频分类方法的正确率及泛化能力，提出一种基于类型标志镜头与视觉词袋模型相结合的体育视频分类方法．首先给出类型标志镜头的定义，并通过类型标志镜头构建该镜头视频帧训练库；然后构建基于视频帧训练库的金字塔视觉词袋模型，将视频帧标志为归一化的词频向量，使用SVM对视频帧进行分类；再通过分析视频帧分类错误的原因及表现形式提出基于时序连续性孤立帧去除算法，以消除视频帧的错误归类．由于体育视频按组合类型可分为单一体育视频与混合体育视频，因此分别提出了单一体育视频及混合体育视频2种分类算法．实验结果表明，文中算法具有实现简单、处理速度快和准确度高的优点．

英文摘要：

Content-based classification of sports video is one of the critical steps in the efficient management of a large number of sports video data. To improve the accuracy and generalization ability of sports video classification, a new sports video classification method based on the combination of marked genre shots and bag of visual words model is proposed. Firstly, the definition of the marked genre shots is given, and the video frame training database of marked genre shots is constructed with the marked genre shots. Secondly, the pyramid visual word bag model is constructed based on the video frame training database, each video frame is represented with a visual words frequency vector, and then the SVM is used to classify the video frame. Subsequently, by analyzing the misclassification causes, the isolated frame removal algorithm is proposed to eliminate the representative frame misclassification. Finally, as the sports video, according to its combination type, can be divided into single sports video and mixed sports video, two different classification algorithms for single sports video and mixed sports video are proposed. Experimental results show that our method has the advantages of simple implementation, fast processing speed and high accuracy.