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Annual Conference on Artificial Intelligence

KI 2002: KI 2002: Advances in Artificial Intelligence pp 253–267Cite as

Axiom — A Modular Visual Object Retrieval System

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 2479))

Abstract

Computer vision has always been an active research domain within artificial intelligence. Recognizing visual objects can alleviate the interaction of users with information retrieval systems. In this paper, we present a modular object recognition system which combines advanced image processing methods with AI techniques in a flexible way. This flexibility permits adaptations to a large variety of tasks. We describe the system architecture, point out some of the key algorithms and present experimental results which demonstrate the system’s performance in several recognition tasks.

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Author information

Authors and Affiliations

  1. Lehrstuhl für Technische Informatik, RWTH Aachen, Germany

    Jochen Wickel, Pablo Alvarado, Peter Dörfler, Thomas Krüger & Karl-Friedrich Kraiss

Authors
  1. Jochen Wickel
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  2. Pablo Alvarado
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  3. Peter Dörfler
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  4. Thomas Krüger
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  5. Karl-Friedrich Kraiss
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Editor information

Editors and Affiliations

  1. Informatik V, RWTH Aachen, Ahornstraße 55, 52056, Aachen, Germany

    Matthias Jarke  & Gerhard Lakemeyer  & 

  2. Computer Science Research, IBM Research Laboratory, Säumerstraße 4, 8803, Rüschlikon, Switzerland

    Jana Koehler

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© 2002 Springer-Verlag Berlin Heidelberg

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Wickel, J., Alvarado, P., Dörfler, P., Krüger, T., Kraiss, KF. (2002). Axiom — A Modular Visual Object Retrieval System. In: Jarke, M., Lakemeyer, G., Koehler, J. (eds) KI 2002: Advances in Artificial Intelligence. KI 2002. Lecture Notes in Computer Science(), vol 2479. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45751-8_17

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  • DOI: https://doi.org/10.1007/3-540-45751-8_17

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-44185-4

  • Online ISBN: 978-3-540-45751-0

  • eBook Packages: Springer Book Archive

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