ABSTRACT
Many techniques have been developed for segmentation and summarization of digital video. The variety of methods is partially due to the fact that different methods work better on different classes of content. Histogram-based segmentation works best on color video with clean cuts; motion-based summarization works best on video with moving cameras and a minimum of disjoint motion. Recognizing that there is no single, best solution for each of these problems has led to the ideas in this chapter for integrating the variety of existing algorithms into a common framework, creating a composite solution that is sensitive to the class of content under analysis, the performance of the algorithms on the specific content, and the best combination of the results. This chapter presents a survey of the existing techniques used to perform video segmentation and summarization and highlights ways in which a composite solution can be developed that adapts to the underlying video content.
