Interactive learning of scene context extractor using combination of bayesian network and logic network

Authors:
Keum-Sung Hwang;Sung-Bae Cho
Affiliations:
Dept. of Computer Science, Yonsei University, Seoul, Korea;Dept. of Computer Science, Yonsei University, Seoul, Korea
Venue:
ACIVS'06 Proceedings of the 8th international conference on Advanced Concepts For Intelligent Vision Systems
Year:
2006

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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.