Advances in Visual Information Management

1. Front Matter

   Pages i-xiii

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2. Advances in Visual Information Management I

   1. Front Matter

      Pages 1-1

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   2. Construction of the Multimedia Mediation Systems

      • Masao Sakauchi

      Pages 3-7

3. Video Retrieval

   1. Front Matter

      Pages 9-9

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   2. A New Algebraic Approach to Retrieve Meaningful Video Intervals from Fragmentarily Indexed Video Shots

      • Sujeet Pradhan, Takashi Sogo, Keishi Tajima, Katsumi Tanaka

      Pages 11-30

   3. Toward The MEdiaSys VIdeo Search Engine (MEVISE)

      • Frédéric Andrès, Kinji Ono, Shin’Ichi Satoh, Nicolas Dessaigne

      Pages 31-44

   4. Content-based Video Retrieval Based on Similarity of Camera Motion

      • Hitoshi Endoh, Ryoji Kataoka

      Pages 45-59

4. Information Visualization

   1. Front Matter

      Pages 61-61

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   2. Visual Exploration for Social Recommendations

      • Junichi Tatemura

      Pages 63-82

   3. Web-Based Visualization of Large Hierarchical Graphs Using Invisible Links in a Hyperbolic Space

      • Ming C. Hao, Meichun Hsu, Umesh Dayal, Adrian Krug

      Pages 83-94

   4. Visualizing Electronic Document Repositories: Drawing Books and Papers in a Digital Library

      • Andreas Rauber, Harald Bina

      Pages 95-114

5. Modeling and Recognition

   1. Front Matter

      Pages 115-115

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   2. A Motion Recognition Method by Using Primitive Motions

      • Ryuta Osaki, Mitsuomi Shimada, Kuniaki Uehara

      Pages 117-127

   3. Conceptual Modelling for Database User Interfaces

      • Richard Cooper, Jo McKirdy, Tony Griffiths, Peter J. Barclay, Norman W. Paton, Philip D. Gray et al.

      Pages 129-138

6. Advances in Visual Information Management II

   1. Front Matter

      Pages 139-139

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   2. Searching, Data Mining and Visualization of Multimedia Data

      • Christos Faloutsos

      Pages 141-142

7. Image Similarity Retrieval

   1. Front Matter

      Pages 143-143

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   2. Efficient Image Retrieval by Examples

      • Roberto Brunelli, Ornella Mich

      Pages 145-162

   3. Applying Augmented Orientation Spatial Similarity Retrieval in Pictorial Database

      • Xiao Ming Zhou, Chuan Heng Ang, Tok Wang Ling

      Pages 163-175

   4. Toward Feature Algebras in Visual Databases: The Case for a Histogram Algebra

      • Amarnath Gupta, Simone Santini

      Pages 177-196

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.

• communication
• database
• information
• information visualization
• multimedia
• tools
• visualization

• Yokohama National University, Japan

  Hiroshi Arisawa

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

  Tiziana Catarci

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