中文摘要：

近年来基于内容的视频检索技术受到人们越来越多的关注，本文提出了一套基于语义匹配的交互式视频检索框架，其贡献主要为以下三方面：1）定义新型的视频高层特征-语义直方图用以描述视频的高层语义信息；2）使用主导集聚类算法建立基于非监督学习的检索机制，用以降低在线计算复杂度和提高检索效率；3）提出新型的相关反馈机制-基于语义的分支反馈，该机制采用分支反馈结构和分支更新策略实现检索性能的提升．实验结果表明了本框架的有效性．

英文摘要：

Content-based video retrieval （CBVR） has attracted increasing interest in recent years. In this paper, we propose a new interactive video retrieval framework using semantic matching. The main contributions are three-fold： 1） We define a novel high-level feature named semantic-matching histogram （SMH） to reflect videos＇ semantic information. 2） We set up an unsupervised learning-based retrieval mechanism using the dominant set clustering for the sake of low online complexity and high retrieval efficiency. 3） We establish a new interactive mechanism called semantic-based relevance feedback （SBRF） working together with SMHs to improve retrieval performances. Experimental results on a database of sports videos show the effectiveness and efficiency of the proposed framework.