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As digital video databases become more and more pervasive, finding video in large databases becomes a major problem. Because of the nature of video (streamed objects), accessing the content of such databases is inherently a time-consuming operation. Enabling intelligent means of video retrieval and rapid video viewing through the processing, analysis, and interpretation of visual content are, therefore, important topics of research. In this paper, we survey the art of video query and retrieval and propose a framework for video-query formulation and video retrieval based on an iterated sequence of navigating, searching, browsing, and viewing. We describe how the rich information media of video in the forms of image, audio, and text can be appropriately used in each stage of the search process to retrieve relevant segments. Also, we address the problem of automatic video annotation—lattaching meanings to video segments to aid the query steps. Subsequently, we present a novel framework of structural video analysis that focuses on the processing of high-level features as well as low-level visual cues. This processing augments the semantic interpretation of a wide variety of long video segments and assists in the search, navigation, and retrieval of video. We describe several such techniques.
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