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Adaptive Object Recognition with Image Feature Interpolation

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AI 2004: Advances in Artificial Intelligence (AI 2004)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3339))

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Abstract

The paper presents a novel image (feature) interpolation method to reinforce the adaptive object recognition system. The system deals with texture images in a sequence according to changing perceptual conditions. When it recognizes several classes of objects under variable conditions, a fundamental problem is that two or more classes are overlapped on the feature space. This interpolation method is useful to resolve the overlapping issue.

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Author information

Authors and Affiliations

  1. College of Electronics and Information Engineering, Sejong University, Seoul, 143-747, Korea

    Sung Wook Baik

  2. Department of Computer Engineering, Honam University, Gwangju, 506-090, Korea

    Ran Baik

Authors
  1. Sung Wook Baik
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  2. Ran Baik
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Editor information

Editors and Affiliations

  1. Faculty of Information Technology, Monash University, VIC 3800, Australia

    Geoffrey I. Webb

  2. Science, Engineering and Technology Portfolio, Royal Melbourne Institute of Technology, VIC 3001, Melbourne, Australia

    Xinghuo Yu

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© 2004 Springer-Verlag Berlin Heidelberg

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Baik, S.W., Baik, R. (2004). Adaptive Object Recognition with Image Feature Interpolation. In: Webb, G.I., Yu, X. (eds) AI 2004: Advances in Artificial Intelligence. AI 2004. Lecture Notes in Computer Science(), vol 3339. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30549-1_83

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  • DOI: https://doi.org/10.1007/978-3-540-30549-1_83

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-24059-4

  • Online ISBN: 978-3-540-30549-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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