Content-based digital video retrieval
Ruud M. Bolle · 1997
All video will eventually become fully digital - there seems to be no way around it. Consequently, digital video databases will become more and more pervasive and finding video in large digital video databases will become a problem just like it is a problem today to find video in analog video databases. The digital form of the video, however, opens up tremendous possibilities. Just like it is possible today to retrieve text documents from large text document databases by querying document content represented by indices, it will become possible to index digital video databases based (semi-)automatically derived indices. In this paper, we address the problem of automatic video annotation - associating semantic meaning with video segments to aid in content-based video retrieval. We present a novel framework of structural video analysis which focuses on the processing of low-level visual data cues to obtain high-level (structural and semantic) video interpretations. Additionally, we propose a flexible framework for video query formulation to aid rapid retrieval of video. This framework is meant to accommodate the depth-first searcher - i.e., the power user, the breath-first searcher, and the casual browser.