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Image and Video Retrieval

5th Internatinoal Conference, CIVR 2006, Tempe, AZ, USA, July 13-15, 2006, Proceedings

  • Conference proceedings
  • © 2006

Overview

Editors:
  1. Hari Sundaram

    1. Arts, Media and Engineering Program, Arizona State University, Tempe,  

  2. Milind Naphade

    1. Intelligent Information Management Department, IBM T.J. Watson Research Center, Hawthorne, USA

  3. John R. Smith

    1. Intelligent Information Management Department, IBM T. J. Watson Research Center, Hawthorne, USA

  4. Yong Rui

    1. Microsoft Corporation, Microsoft China R&D Group, Beijing, China

Part of the book series: Lecture Notes in Computer Science (LNCS, volume 4071)

Part of the book sub series: Information Systems and Applications, incl. Internet/Web, and HCI (LNISA)

Included in the following conference series:

Conference proceedings info: CIVR 2006.

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About this book

This volume contains the proceeding of the 5th International Conference on - age and Video Retrieval (CIVR), July 13–15, 2006, Arizona State University, Tempe, AZ, USA: http://www. civr2006. org. Image and video retrieval cont- ues to be one of the most exciting and fast-growing research areas in the ?eld of multimedia technology. However, opportunities for exchanging ideas between researchers and users of image and video retrieval systems are still limited. The InternationalConferenceonImageandVideo Retrieval(CIVR)hastakenonthe mission of bringing together these communities to allow researchers and prac- tioners around the world to share points of view on image and video retrieval. A uniquefeatureoftheconferenceistheemphasisonparticipationfrompractiti- ers. The objective is to illuminate critical issues and energize both communities for the continuing exploration of novel directions for image and video retrieval. We receivedover 90 submissions for the conference. Eachpaper wascarefully reviewed by three members of the program committee, and then checked by one of the program chairs and/or general chairs. The program committee consisted of more than 40 experts in image and video retrieval from Europe, Asia and North America, and we drew upon approximately 300 high-quality reviews to ensure a thorough and fair review process. The paper submission and review process was fully electronic, using the EDAS system. The quality of the submitted papers was very high, forcing the committee members to make some di?cult decisions. Due to time and space constraints, we could only accept 18 oral papers and 30 poster papers.

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Table of contents (65 papers)

  1. Front Matter

    Download chapter PDF

  2. Session O1: Interactive Image and Video Retrieval

    1. Interactive Experiments in Object-Based Retrieval

      • Sorin Sav, Gareth J. F. Jones, Hyowon Lee, Noel E. O’Connor, Alan F. Smeaton
      Pages 1-10

    2. Learned Lexicon-Driven Interactive Video Retrieval

      • Cees Snoek, Marcel Worring, Dennis Koelma, Arnold Smeulders
      Pages 11-20

    3. Mining Novice User Activity with TRECVID Interactive Retrieval Tasks

      • Michael G. Christel, Ronald M. Conescu
      Pages 21-30

  3. Session O2: Semantic Image Retrieval

    1. A Linear-Algebraic Technique with an Application in Semantic Image Retrieval

      • Jonathon S. Hare, Paul H. Lewis, Peter G. B. Enser, Christine J. Sandom
      Pages 31-40

    2. Logistic Regression of Generic Codebooks for Semantic Image Retrieval

      • João Magalhães, Stefan Rüger
      Pages 41-50

    3. Query by Semantic Example

      • Nikhil Rasiwasia, Nuno Vasconcelos, Pedro J. Moreno
      Pages 51-60

  4. Session O3: Visual Feature Analysis

    1. Corner Detectors for Affine Invariant Salient Regions: Is Color Important?

      • Nicu Sebe, Theo Gevers, Joost van de Weijer, Sietse Dijkstra
      Pages 61-71

    2. Keyframe Retrieval by Keypoints: Can Point-to-Point Matching Help?

      • Wanlei Zhao, Yu-Gang Jiang, Chong-Wah Ngo
      Pages 72-81

    3. Local Feature Trajectories for Efficient Event-Based Indexing of Video Sequences

      • Nicolas Moënne-Loccoz, Eric Bruno, Stéphane Marchand-Maillet
      Pages 82-91

  5. Session O4: Learning and Classification

    1. A Cascade of Unsupervised and Supervised Neural Networks for Natural Image Classification

      • Julien Ros, Christophe Laurent, Grégoire Lefebvre
      Pages 92-101

    2. Bayesian Learning of Hierarchical Multinomial Mixture Models of Concepts for Automatic Image Annotation

      • Rui Shi, Tat-Seng Chua, Chin-Hui Lee, Sheng Gao
      Pages 102-112

    3. Efficient Margin-Based Rank Learning Algorithms for Information Retrieval

      • Rong Yan, Alexander G. Hauptmann
      Pages 113-122

  6. Session O5: Image and Video Retrieval Metrics

    1. Leveraging Active Learning for Relevance Feedback Using an Information Theoretic Diversity Measure

      • Charlie K. Dagli, Shyamsundar Rajaram, Thomas S. Huang
      Pages 123-132

    2. Video Clip Matching Using MPEG-7 Descriptors and Edit Distance

      • Marco Bertini, Alberto Del Bimbo, Walter Nunziati
      Pages 133-142

    3. Video Retrieval Using High Level Features: Exploiting Query Matching and Confidence-Based Weighting

      • Shi-Yong Neo, Jin Zhao, Min-Yen Kan, Tat-Seng Chua
      Pages 143-152

  7. Session O6: Machine Tagging

    1. Annotating News Video with Locations

      • Jun Yang, Alexander G. Hauptmann
      Pages 153-162

    2. Automatic Person Annotation of Family Photo Album

      • Ming Zhao, Yong Wei Teo, Siliang Liu, Tat-Seng Chua, Ramesh Jain
      Pages 163-172

    3. Finding People Frequently Appearing in News

      • Derya Ozkan, Pınar Duygulu
      Pages 173-182

  8. Session P1: Poster I

    1. A Novel Framework for Robust Annotation and Retrieval in Video Sequences

      • Arasanathan Anjulan, Nishan Canagarajah
      Pages 183-192
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Other volumes

  1. Image and Video Retrieval

Editors and Affiliations

  • Arts, Media and Engineering Program, Arizona State University, Tempe,  

    Hari Sundaram

  • Intelligent Information Management Department, IBM T.J. Watson Research Center, Hawthorne, USA

    Milind Naphade

  • Intelligent Information Management Department, IBM T. J. Watson Research Center, Hawthorne, USA

    John R. Smith

  • Microsoft Corporation, Microsoft China R&D Group, Beijing, China

    Yong Rui

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