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Interactive Learning of Scene Context Extractor Using Combination of Bayesian Network and Logic Network

  • Keum-Sung Hwang
  • Sung-Bae Cho
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4179)

Abstract

The vision-based scene understanding technique that infers scene-interpreting contexts from real-world vision data has to not only deal with various uncertain environments but also reflect user’s requests. Especially, learnability is a hot issue for the system. In this paper, we adopt a probabilistic approach to overcome the uncertainty, and propose an interactive learning method using combination of Bayesian network and logic network to reflect user’s requirements in real-time. The logic network works for supporting logical inference of Bayesian network. In the result of some learning experiments using interactive data, we have confirmed that the proposed interactive learning method is useful for scene context reasoning.

Keywords

Bayesian Network Logic Network Logical Inference Scene Context Scene Understanding 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Keum-Sung Hwang
    • 1
  • Sung-Bae Cho
    • 1
  1. 1.Dept. of Computer ScienceYonsei UniversitySeoulKorea

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