Scene Segmentation and Semantic Representation for High-Level Retrieval

In this letter, a novel framework to segment video scene and represent scene content is proposed. Firstly, video shots are detected using a rough-to-fine algorithm. Secondly, key frames are selected adaptively, and redundant key frames are removed using template matching. Then, spatio-temporal coherent shots are clustered into the same scene. Finally, under the full analysis of typical characters on continuously recorded videos, video scene content is semantically represented to satisfy human demand on video retrieval. Experimental results show the proposed method makes sense to efficient retrieval of video content of interest.