Activity-Object bayesian networks for detecting occluded objects in uncertain indoor environment

Authors:
Youn-Suk Song;Sung-Bae Cho;Il Hong Suh
Affiliations:
Dept. of Computer Science, Yonsei University, Seoul, Korea;Dept. of Computer Science, Yonsei University, Seoul, Korea;The College of Information & Communications, Hanyang University, Seoul, Korea
Venue:
KES'05 Proceedings of the 9th international conference on Knowledge-Based Intelligent Information and Engineering Systems - Volume Part III
Year:
2005

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Abstract

In the field of the service robots, object detection and scene understanding are very important. Conventional methods for object detection are performed with the geometric models, but they have limitations to be used in the uncertain and dynamic environments. This paper proposes a method to predict the probability of target object with Bayesian networks modeled based on activity-object relations. Experiments in indoor office environment show the usefulness of the proposed method for object detection, which produces about 86.5% of accuracy with environments.