Advances in Visual Information Systems

1. Shape-Based Retrieval

   1. Wavelet-Based Salient Points: Applications to Image Retrieval Using Color and Texture Features

      • Etienne Loupias, Nicu Sebe

      Pages 223-232

   2. Matching Shapes with Self-intersections

      • Sadegh Abbasi, Farzin Mokhtarian

      Pages 233-243

2. Image Databases

   1. A Novel Approach for Accessing Partially Indexed Image Corpora

      • Gérald Duffing, Malika SmaÏl

      Pages 244-256

   2. Show Me What You Mean! PARISS: A CBIR-Interface That Learns by Example

      • G Caenen, G Frederix, A.A.M Kuijk, E.J Pauwels, B.A.M Schouten

      Pages 257-268

   3. Scale Summarized and Focused Browsing of Primitive Visual Content

      • Xenophon Zabulis, Jon Sporring, Stelios C. Orphanoudakis

      Pages 269-278

   4. Integrated Browsing and Searching of Large Image Collections

      • Zoran Pečenovió, Minh N. Do, Martin Vetterli, Pearl Pu

      Pages 279-289

   5. A Rich Get Richer Strategy for Content-Based Image Retrieval

      • Lijuan Duan1, Wen Gao, Jiyong Ma

      Pages 290-299

   6. MRML: A Communication Protocol for Content-Based Image Retrieval

      • Wolfgang Müller, Henning Müller, Stéphane Marchand-Maillet, Thierry Pun, David McG. Squire, Zoran Pečenović et al.

      Pages 300-311

   7. An Integrated Multimedia System with Learning Capabilities

      • G. Ciocca, I. Gagliardi, R. Schettini, B. Zonta

      Pages 312-326

3. Video Indexing

   1. Global Motion Fourier Series Expansion for Video Indexing and Retrieval

      • E. Bruno, D. Pellerin

      Pages 327-337

   2. Feature Driven Visualization of Video Content for Interactive Indexing

      • Jeroen Vendrig, Marcel Worring

      Pages 338-348

   3. Conceptual Indexing of Television Images Based on Face and Caption Sizes and Locations

      • Remi Ronfard, Christophe Garcia, Jean Carrive

      Pages 349-359

4. Image Databases

   1. SIMPLIcity: Semantics-sensitive Integrated Matching for Picture LIbraries

      • James Z. Wang, Jia Li, Gio Wiederholdy

      Pages 360-371

   2. Semantic Indexing for Image Retrieval Using Description Logics

      • Eugenio Di Sciascio, Francesco M. Donini, Marina Mongiello

      Pages 372-383

   3. An Iconic and Semantic Content Based Retrieval System for Histological Images

      • Ringo W. K. Lam, Kent K. T. Cheung, Horace H. S. Ip, Lilian H. Y. Tang, R. Hanka

      Pages 384-395

5. Image Retrieval

   1. Image Retrieval by Colour and Texture Using Chromaticity Histograms and Wavelet Frames

      • Spyros Liapis, Georgios Tziritas

      Pages 397-406

   2. Adaptive Multi-Class Metric Content-Based Image Retrieval

      • Jing Peng

      Pages 407-418

   3. Integrating Visual and Textual Cues for Image Classification

      • Theo Gevers, Frank Aldershoff, Jan-Mark Geusebroek

      Pages 419-429

6. Benchmarking

   1. Evaluating the Performance of Content-Based Image Retrieval Systems

      • Markus Koskela, Jorma Laaksonen, Sami Laakso, Erkki Oja

      Pages 430-441

   2. Benchmarking for Content-Based Visual Information Search

      • C. H. C. Leung, H. H. S. Ip

      Pages 442-456

Presently, in our world, visual information dominates. The turn of the millenium marks the age of visual information systems. Enabled by picture sensors of all kinds turning digital, visual information will not only enhance the value of existing information, it will also open up a new horizon of previously untapped information sources. There is a huge demand for visual information access from the consumer. As well, the handling of visual information is boosted by the rapid increase of hardware and Internet capabilities. Advanced technology for visual information systems is more urgently needed than ever before: not only new computational methods to retrieve, index, compress and uncover pictorial information, but also new metaphors to organize user interfaces. Also, new ideas and algorithms are needed which allow access to very large databases of digital pictures and videos. Finally we should not forget new systems with visual interfaces integrating the above components into new types of image, video or multimedia databases and hyperdocuments. All of these technologies will enable the construction of systems that are radically different from conventional information systems. Many novel issues will need to be addressed: query formulation for pictorial information, consistency management thereof, indexing and assessing the quality of these systems. Historically, the expression Visual Information Systems can be understood either as a system for image information or as visual system for any kind information.

• Animation
• Augmented Reality
• Benchmarking
• Hidden Markov Model
• Markov Model
• Multimedia
• Visual Information
• classification
• database
• filtering
• image processing
• image retrieval
• multimedia information systems
• visual information systems
• visualization

• Claude Bernard University of Lyon, Villeurbanne Cedex, France

  Robert Laurini

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