关键词: 镜头分类, 事务序列, 事务数据库, 视频关联挖掘, 精彩事件

Abstract: Based on transaction sequence, an association mining method is proposed for soccer video summarization mining. The processing progress is divided into three steps which are video data preprocessing, video feature extraction and video summarization mining. In the first step, the original video flow is segmented into physical shots. During the second step, the video is transferred into shot identifier sequence through classifying the physical shots into five classes. The shot identifier sequence is segmented into transaction sequences and a transaction database is constructed for storing transaction sequences. The traditional APRIORI algorithm is applied to mining the transaction database to obtain association patterns, which are used to form video summarization in the last step. The experimental results show that the proposed method is practical because it has achieved high rates of recall and precision.

Key words: shot classification, transaction sequence, transaction database, video association mining, highlights