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Video Content Analysis Using Multimodal Information: For Movie Content Extraction, Indexing and Representation 1st ed. Softcover of orig. ed. 2003 [Pehme köide]

  • Formaat: Paperback / softback, 194 pages, kõrgus x laius: 235x155 mm, kaal: 700 g, XXIII, 194 p., 1 Paperback / softback
  • Ilmumisaeg: 07-Dec-2010
  • Kirjastus: Springer-Verlag New York Inc.
  • ISBN-10: 1441953655
  • ISBN-13: 9781441953650
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  • Formaat: Paperback / softback, 194 pages, kõrgus x laius: 235x155 mm, kaal: 700 g, XXIII, 194 p., 1 Paperback / softback
  • Ilmumisaeg: 07-Dec-2010
  • Kirjastus: Springer-Verlag New York Inc.
  • ISBN-10: 1441953655
  • ISBN-13: 9781441953650
With the fast growth ofmultimedia information, content-based video anal­ ysis, indexing and representation have attracted increasing attention in re­ cent years. Many applications have emerged in these areas such as video­ on-demand, distributed multimedia systems, digital video libraries, distance learning/education, entertainment, surveillance and geographical information systems. The need for content-based video indexing and retrieval was also rec­ ognized by ISOIMPEG, and a new international standard called "Multimedia Content Description Interface" (or in short, MPEG-7)was initialized in 1998 and finalized in September 2001. In this context, a systematic and thorough review ofexisting approaches as well as the state-of-the-art techniques in video content analysis, indexing and representation areas are investigated and studied in this book. In addition, we will specifically elaborate on a system which analyzes, indexes and abstracts movie contents based on the integration ofmultiple media modalities. Content ofeach part ofthis book is briefly previewed below. In the first part, we segment a video sequence into a set ofcascaded shots, where a shot consistsofone or more continuouslyrecorded image frames. Both raw and compressedvideo data will beinvestigated. Moreover, consideringthat there are always non-story units in real TV programs such as commercials, a novel commercial break detection/extraction scheme is developed which ex­ ploits both audio and visual cues to achieve robust results. Specifically, we first employ visual cues such as the video data statistics, the camera cut fre­ quency, and the existenceofdelimiting black frames between commercials and programs, to obtain coarse-level detection results.

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1. Introduction.-
2. Background and Previous Work.-
3. Video Content
Pre-Processing.-
4. Content-Based Movie Scene and Event Extraction.-
5.
Speaker Identification for Movies.-
6. Scene-Based Movie Summarization.-
7.
Event-Based Movie Skimming.-
8. Conclusion and Future Work.- References.