Perceptual synoptic view-based video retrieval using metadata

Content-based video retrieval and video synopsis are generally considered as two different areas. In this paper, we present an efficient approach for video retrieval based on the perceptual synopsis database of the videos. Video synopsis encapsulates an overview of a shot in a single frame. This is the first time video synopsis is used for video indexing providing the user an intuitive link for accessing actions in the video. We propose an enhanced synopsis called meta synopsis for the video database index, which will contain all essential information for retrieval. Various information such as background of a scene, motion trajectory of the foreground objects, color, texture, and mutual information in the synopsis database will empower us to retrieve relevant video content from huge video databases. Experiments were conducted on the OVP, BBC Motion Gallery, TRECVID data set, and other videos. Instead of using key frames as the query frames, the method accepts any arbitrary query frames. The experimental results illustrate that our proposed method can accurately identify a pertinent video from huge video databases.