Performance Characterization in Computer Vision

  • Reinhard Klette
  • H. Siegfried Stiehl
  • Max A. Viergever
  • Koen L. Vincken

Part of the Computational Imaging and Vision book series (CIVI, volume 17)

Table of contents

  1. Front Matter
    Pages i-xvi
  2. General Issues

    1. Front Matter
      Pages 1-1
    2. Adrian F. Clark, Patrick Courtney
      Pages 29-40
    3. Radek Mařík
      Pages 41-51
  3. Methodical Aspects

  4. Statistical Aspects

    1. Front Matter
      Pages 93-93
    2. Robert M. Haralick
      Pages 95-114
    3. Peter Meer, Bogdan Matei, Kyujin Cho
      Pages 115-124
  5. Comparative Studies

    1. Front Matter
      Pages 137-137
    2. Ryszard Kozera, Reinhard Klette
      Pages 153-166
    3. Judit Verestóy, Dmitry Chetverikov
      Pages 167-178
  6. Selected Methods and Algorithms

    1. Front Matter
      Pages 179-179
    2. Joachim M. Buhmann, Jan Puzicha
      Pages 195-209
    3. Atsushi Imiya, Kazuhiko Kawamoto
      Pages 227-240
    4. Reinhard Klette, Feng Wu, Shao-Zheng Zhou
      Pages 241-253
    5. Maria Petrou, Nikolaos Georgis, Josef Kittler
      Pages 255-264
  7. Domain-specific Evaluation: Medical Imaging

    1. Front Matter
      Pages 273-273
    2. Wiro J. Niessen, Carolien J. Bouma, Koen L. Vincken, Max A. Viergever
      Pages 275-284
    3. Karl Rohr, H. Siegfried Stiehl, Sönke Frantz, Thomas Hartkens
      Pages 285-297
    4. Koen L. Vincken, André S. E. Koster, Cornelis N. De Graaf, Max A. Viergever
      Pages 299-311
  8. Back Matter
    Pages 313-317

About this book


This edited volume addresses a subject which has been discussed inten­ sively in the computer vision community for several years. Performance characterization and evaluation of computer vision algorithms are of key importance, particularly with respect to the configuration of reliable and ro­ bust computer vision systems as well as the dissemination of reconfigurable systems in novel application domains. Although a plethora of literature on this subject is available for certain' areas of computer vision, the re­ search community still faces a lack of a well-grounded, generally accepted, and--eventually-standardized methods. The range of fundamental problems encoIl!passes the value of synthetic images in experimental computer vision, the selection of a representative set of real images related to specific domains and tasks, the definition of ground truth given different tasks and applications, the design of experimental test­ beds, the analysis of algorithms with respect to general characteristics such as complexity, resource consumption, convergence, stability, or range of admissible input data, the definition and analysis of performance measures for classes of algorithms, the role of statistics-based performance measures, the generation of data sheets with performance measures of algorithms sup­ porting the system engineer in his configuration problem, and the validity of model assumptions for specific applications of computer vision.


3D Analysis Computer Vision Image segmentation Optical flow Performance Stereo algorithms computer computer science database image processing

Editors and affiliations

  • Reinhard Klette
    • 1
  • H. Siegfried Stiehl
    • 2
    • 3
  • Max A. Viergever
    • 4
  • Koen L. Vincken
    • 4
  1. 1.Department of Computer Science, Tamaki CampusThe University of AucklandAucklandNew Zealand
  2. 2.Cognitive Systems Research Group, Department of Computer ScienceUniversity of HamburgHamburgGermany
  3. 3.FB Informatik AB Kognitive SystemeUniversität HamburgHamburgGermany
  4. 4.Image Sciences InstituteUniversity Medical Center UtrechtUtrechtThe Netherlands

Bibliographic information

  • DOI
  • Copyright Information Springer Science+Business Media B.V. 2000
  • Publisher Name Springer, Dordrecht
  • eBook Packages Springer Book Archive
  • Print ISBN 978-90-481-5487-6
  • Online ISBN 978-94-015-9538-4
  • Series Print ISSN 1381-6446
  • Buy this book on publisher's site
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