A New Interactive Video Retrieval Framework Using Semantic Matching
基于语义匹配的交互式视频检索框架

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 on- line 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.