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Advances in Visual Information Management

Visual Database Systems. IFIP TC2 WG2.6 Fifth Working Conference on Visual Database Systems May 10–12, 2000, Fukuoka, Japan

  • Book
  • © 2000

Overview

Editors:
  1. Hiroshi Arisawa

    1. Yokohama National University, Japan

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    You can also search for this editor in PubMed   Google Scholar

  2. Tiziana Catarci

    1. Università degli Studi di Roma “La Sapienza”, Italy

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    You can also search for this editor in PubMed   Google Scholar

Part of the book series: IFIP Advances in Information and Communication Technology (IFIPAICT, volume 40)

Included in the following conference series:

Conference proceedings info: VDB 2000.

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Table of contents (24 chapters)

  1. Spatio-Temporal Database

    1. Front Matter

      Pages 197-197
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    2. Query-by-Trace: Visual Predicate Specification in Spatio-Temporal Databases

      • Martin Erwig, Markus Schneider
      Pages 199-218

    3. Skimming Multiple Perspective Video Using Tempo-Spatial Importance Measures

      • Toshihiko Hata, Tatsuo Hirose, Katsumi Tanaka
      Pages 219-238

    4. Networked Augmented Spatial Hypermedia System on Internet

      • Michihiro Murao, Masatoshi Arikawa, Koji Okamura
      Pages 239-253

  2. Visual Querying

    1. Front Matter

      Pages 255-255
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    2. Drag and Drop: Amalgamation of Authoring, Querying, and Restructuring for Multimedia View Construction

      • Atsuyuki Morishima, Seiichi Koizumi, Hiroyuki Kitagawa
      Pages 257-276

    3. BBQ: A Visual Interface for Integrated Browsing and Querying of XML

      • Kevin D. Munroe, Yannis Papakonstantiou
      Pages 277-296

    4. MDDQL: A Visual Query Language for Metadata Driven Querying

      • E. Kapetanios, M. C. Norrie, D. Fuhrer-Stakic
      Pages 297-316

  3. Clustering and Retrieval

    1. Front Matter

      Pages 317-317
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    2. Hierarchical Space Model for Multimedia Data Retrieval

      • Makoto Onizuka, Shuichi Nishioka
      Pages 319-328

    3. MST Construction with Metric Matrix for Clustering

      • Masahiro Ishikawa, Yi Liu, Kazutaka Furuse, Hanxiong Chen, Nobuo Ohbo
      Pages 329-338

  4. User Interface

    1. Front Matter

      Pages 339-339
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    2. Automatic Updates of Interactive Information Visualization User Interfaces through Database Triggers

      • Martin Leissler, Matthias Hemmje, Erich Neuhold
      Pages 341-366

    3. TBE: A Graphical Interface for Writing Trigger Rules in Active Databases

      • Dongwon Lee, Wenlei Mao, Henry Chiu, Wesley W. Chu
      Pages 367-386

    4. WebSA: Database Support for Efficient Web Site Navigation

      • Isabel F. Cruz, Lijun Leo Liu, Tony Y. Wu
      Pages 387-406

  5. Back Matter

    Pages 407-410
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Keywords

About this book

Video segmentation is the most fundamental process for appropriate index­ ing and retrieval of video intervals. In general, video streams are composed 1 of shots delimited by physical shot boundaries. Substantial work has been done on how to detect such shot boundaries automatically (Arman et aI. , 1993) (Zhang et aI. , 1993) (Zhang et aI. , 1995) (Kobla et aI. , 1997). Through the inte­ gration of technologies such as image processing, speech/character recognition and natural language understanding, keywords can be extracted and associated with these shots for indexing (Wactlar et aI. , 1996). A single shot, however, rarely carries enough amount of information to be meaningful by itself. Usu­ ally, it is a semantically meaningful interval that most users are interested in re­ trieving. Generally, such meaningful intervals span several consecutive shots. There hardly exists any efficient and reliable technique, either automatic or manual, to identify all semantically meaningful intervals within a video stream. Works by (Smith and Davenport, 1992) (Oomoto and Tanaka, 1993) (Weiss et aI. , 1995) (Hjelsvold et aI. , 1996) suggest manually defining all such inter­ vals in the database in advance. However, even an hour long video may have an indefinite number of meaningful intervals. Moreover, video data is multi­ interpretative. Therefore, given a query, what is a meaningful interval to an annotator may not be meaningful to the user who issues the query. In practice, manual indexing of meaningful intervals is labour intensive and inadequate.

Editors and Affiliations

  • Yokohama National University, Japan

    Hiroshi Arisawa

  • Università degli Studi di Roma “La Sapienza”, Italy

    Tiziana Catarci

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