By Yiannis Kompatsiaris, Bernard Merialdo, Shiguo Lian
The quick development of electronic multimedia applied sciences has not just revolutionized the creation and distribution of audiovisual content material, but additionally created the necessity to successfully examine television courses to let purposes for content material managers and shoppers. Leaving no stone unturned, TV content material research: concepts and Applications presents a close exploration of television software research techniques.
Leading researchers and lecturers from worldwide offer scientifically sound remedy of contemporary advancements around the comparable topic areas—including platforms, architectures, algorithms, functions, study effects, rising techniques, and open concerns. The publication is equipped into six components:
- Content Extraction - deals with automated research and annotation of television content material, addressing typical semantics and ideas in addition to television content
- Content Structuring - examines thoughts for picking fascinating components of television courses and offering direct entry to it
- Content suggestion - explores the matter of offering clients with the main correct content material, addressing the matter of an ever-increasing volume of obtainable content material
- Content caliber - considers visible notion and caliber methods within the multi-display television context and the categorical cellular television scenario
- Web and Social television - presents stories on internet and television convergence and on how user-generated content material in internet 2.0 functions can be utilized to reinforce services
- Content creation - covers postproduction, visible results, and presentation standards
Most components begin with a bankruptcy that gives an outline of that quarter, via state of the art ways concentrating on particular matters lined in that part. Reporting on contemporary advances within the box, the booklet provide you with the worldwide view and up to date knowing of rising traits had to perform the advance of the electronic television domain.
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Additional info for TV Content Analysis: Techniques and Applications
Sample text
Each key identifier is stored inside the corresponding hash bucket together with an additional check-sum hash to discriminate between different features within the same bucket (see [14]). Finally, when the database has been created, we further divide the list of ordered buckets into fixed-size blocks and record the offsets to each block, together with the bucket index at the start of that block. Instead of linearly reading all buckets that make up the database in order to find the matches to each query feature hash in the batch, the offsets are used to compute the next possible block that could contain a matching hash value.
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 10 11 12 13 13 14 16 17 18 22 22 23 Detecting (near) copies of video footage in streams or databases has several useful applications. Reuse of video material by different data aggregators can help as a guide to link stories across channels, while finding copies of copyrighted video fragments is of great interest for their rightful owners.
ACM Press, 2004. 5. P. Dollár, V. Rabaud, G. Cottrell, and S. Belongie. Behavior recognition via sparse spatio-temporal features. In VSPETS’05, Beijing, China, pp. 65–72, 2005. 6. M. Douze, A. Gaidon, H. Jégou, M. Marszałek, and C. Schmid. Inria-lears video copy detection system. In TRECVID Workshop, November 17–18, 2008, Gaithersburg, MD. 7. C. Harris and M. Stephens. A combined corner and edge detector. , pp. 147–151, 1988. 8. -S. Hua, X. -J. Zhang. Robust video signature based on ordinal measure.