A proposal for a video content generation support system and its application

A video content generation support system, based on an interactive approach that maps low-level features to high-level concepts, is proposed. By consulting an ontological semantic object model database, the same semantic objects such as characters, backgrounds, and the main subjects in key frames of each video shots can be queried and automatically annotated based on the similarity of low-level features such as the color, area, and position of each region. Since image recognition techniques are limited in their ability to fully identify and compare images, an additional function is proposed, which uses a coarse model to recover a higher number of similar key frames to provide more relevant results. The content provider can then select relevant key frames interactively from the results to annotate matched objects in them according to the descriptions that are added into the model. Therefore, more complex content can be generated with a higher accuracy by using a combination of the application-oriented operations. The system has high potential for use in object-based interactive multimedia applications. One prototype application is also presented.