Semantic video database system with semi-automatic secondary-content generation capability

摘要

A semantic video database system, based on an interactive approach that maps low-level features to high-level concepts, is proposed. A database of ontological semantic object models allows the user to get information about specific semantic objects, such as certain actors or other features of a TV drama. The system searches the database for key frames within the video to detect similarities in detailed or "low-level" features, such as the color, area, and position of a specific part of the frame. Since image recognition techniques are limited in their ability to fully identify and compare images, we propose an additional function in which a coarse model is used to recover a greater number of similar key frames, thus providing more relevant results. From these results, the content provider can select relevant key frames interactively; the matched objects in them are then automatically annotated according to descriptions that are added into the model by content provider. Therefore, more complex content can be generated with greater accuracy by using a combination of application-oriented operations. The system has high potential for use in object-based interactive multimedia applications. We also present an object-based video content generation application called the Drama Characters' Popularity Voting System.