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This paper discusses the implementation of a database buffer manager as a component of a DBMS. The interface between calling components of higher system layers and the buffer manager is described; the principal differences between virtual memory paging and database buffer management are outlined; the notion of referencing versus addressing of database pages is introduced; and the concept of fixing pages in the buffer to prevent uncontrolled replacement is explained. Three basic tasks have to be performed by the buffer manager: buffer search, allocation of frames to concurrent transactions, and page replacement. For each of these tasks, implementation alternatives are discussed and illustrated by examples from a performance evaluation project of a CODASYL DBMS.

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Film genres in digital video can be detected automatically. In a three-step approach we analyze first the syntactic properties of digital films: color statistics, cut detection, camera motion, object motion and audio. In a second step we use these statistics to derive at a more abstract level film style attributes such as camera panning and zooming, speech and music. These are distinguishing properties for film genres, e.g. newscasts vs. sports vs. commercials. In the third and final step we map the detected style attributes to film genres. Algorithms for the three steps are presented in detail, and we report on initial experience with real videos. It is our goal to automatically classify the large body of existing video for easier access in digital video-on-demand databases.

Large video on demand databases consisting of thousands of digital movies are not easy to handle: the user must have an attractive means to retrieve his movie of choice. For analog video, movie trailers are produced to allow a quick preview and perhaps stimulate possible buyers. This paper presents techniques to automatically produce such m o vie abstracts of digtial videos.

Efficient indexing and retrieval of digital video is an important function of video databases. One powerful index for retrieval is the text appearing in them. It enables content-based browsing. We present our new methods for automatic segmentation of text in digital videos. The algorithms we propose make use of typical characteristics of text in videos in order to enable and enhance segmentation performance. The unique features of our approach are the tracking of characters and words over their complete duration of occurrence in a video and the integration of the multiple bitmaps of a character over time into a single bitmap. The output of the text segmentation step is then directly passed to a standard OCR software package in order to translate the segmented text into ASCII. Also, a straightforward indexing and retrieval scheme is introduced. It is used in the experiments to demonstrate that the proposed text segmentation algorithms together with existing text recognition algorithms are suitable for indexing and retrieval of relevant video sequences in and from a video database. Our experimental results are very encouraging and suggest that these algorithms can be used in video retrieval applications as well as to recognize higher level semantics in videos.