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2005
Springer

Activity-Object Bayesian Networks for Detecting Occluded Objects in Uncertain Indoor Environment

9 years 7 months ago
Activity-Object Bayesian Networks for Detecting Occluded Objects in Uncertain Indoor Environment
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.
Youn-Suk Song, Sung-Bae Cho, Il Hong Suh
Added 28 Jun 2010
Updated 28 Jun 2010
Type Conference
Year 2005
Where KES
Authors Youn-Suk Song, Sung-Bae Cho, Il Hong Suh
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