教学视频的文本语义镜头分割和标注

摘要

为了对教学视频这一专门类别视频进行自动标注，本文首先提取视频中的字幕信息，通过文本预处理后，使用视频中的字幕文本信息内容结合潜在狄利克雷分布（Latent Dirichlet allocation ，LDA ）主题模型方法获得视频镜头在主题上的概率分布，通过计算主题概率分布差异，进行语义层面镜头分割。然后以镜头为样本，使用安全的半监督支持向量机（Safe semi‐supervised support vector machine ， S4VM ）方法，通过少量的标注镜头样本，完成对未标注镜头的自动标注。实验结果表明，本文方法利用字幕文本信息和LDA模型，有效完成了视频的语义镜头分割，不仅可以对镜头完成标注，而且可以对整个视频进行关键词标注。%To automatically annotate a special kind of video ,i .e .,lecture videos ,a method is proposed to extract caption information from video ,Then subtitle information is utilized with latent Dirichlet alloca‐tion(LDA) .The document distribution probability on the topics is obtained .The distance between these probability distributions is calculated .Finally the semantic shot segmentation is realized .A shot is set as a sample based on safe semi‐supervised support vector machine(S4VM ) method .A small amount of la‐beled semantic shots are taken as samples .The unlabeled shots are automatically annotated .Experimen‐tal results show that the proposed method can not only effectively complete the shot semantic segmenta‐tion ,but also annotate key words for the video .