By Ahmed K. Elmagarmid, Haitao Jiang, Abdelsalam A. Helal, Anupam Joshi, Magdy Ahmed
Nice advances were made within the database box. Relational and item- orientated databases, dispensed and client/server databases, and large-scale info warehousing are one of the extra extraordinary. besides the fact that, none of those advances grants to have as nice and direct an impact at the day-by-day lives of normal electorate as video databases. Video databases will offer a quantum bounce in our skill to house visible facts, and in permitting humans to entry and control visible details in methods hitherto concept very unlikely. Video Database platforms: matters, items and functions offers functional details on educational learn concerns, advertisement items that experience already been built, and the functions of the longer term riding this learn and improvement. This ebook can be thought of a reference textual content for these coming into the sector of video or multimedia databases, in addition to a reference for practitioners who are looking to establish the categories of goods wanted with the intention to make the most of video databases. Video Database platforms: matters, items and functions covers recommendations, items and functions. it really is written at a degree that is much less exact than that usually present in textbooks yet extra in-depth than that as a rule written in exchange press or expert reference books. hence, it seeks to serve either an educational and commercial viewers by way of delivering a unmarried resource of data in regards to the learn concerns within the box, and the state of the art of perform.
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Extra resources for Video Database Systems: Issues, Products, and Applications
D (DC-coded) frames are coded using DC coefficients of blocks; thus, they contain only low-frequency information. D frames are not allowed to coexist with I / P / B frames and are rarely used in practice. 26 CHAPTER 2 Obviously, any M P E G compressed video stream must have at least I frames. The data-size ratios between frames suggested by the standard are 3:1 for I:P and 5:2 to 2:1 for P:B. In other words, B frames have the highest degree of compression, and I frames have the least. More details about MPEG video streams can be found in .
One fundamental aspect that has a great impact on all these problems is the content-based temporal sampling of video data . Its purpose is to identify significant video frames to achieve better representation, indexing, storage, and retrieval of the video data. Automatic content-based temporal sampling is very difficult due to the fact that the sampling criteria are not well defined, that is, whether a video frame is i m p o r t a n t or not is usually subjective. Moreover, it is usually highly application-dependent and requires high-level, semantic interpretation of the video content.
The weakness of this approach is that video segmentation and annotation are all done manually, which can be very tedious. Similarly, Ioka and Kurokawa  also addressed the problem of indexing image sequences based on motion properties of objects within the sequences. Motion vectors of objects in a video sequence are automatically extracted using a block motion estimation technique. Vectors are then m a p p e d by using spatiotemporal space ( x - y - t ) and are aggregated into several representative vectors using statistical analysis.
Video Database Systems: Issues, Products, and Applications by Ahmed K. Elmagarmid, Haitao Jiang, Abdelsalam A. Helal, Anupam Joshi, Magdy Ahmed