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FSKD
2006
Springer

Context Modeling with Bayesian Network Ensemble for Recognizing Objects in Uncertain Environments

9 years 1 months ago
Context Modeling with Bayesian Network Ensemble for Recognizing Objects in Uncertain Environments
Abstract. It is difficult to understand a scene from visual information in uncertain real world. Since Bayesian network (BN) is known as good in this uncertainty, it has received significant attention in the area of vision-based scene understanding. However, BN-based modeling methods still have the difficulties in modeling complex relationships and combining several modules, as well as the high computational complexity of inference. To overcome them, this paper proposes a method to divide and select the BN modules for recognizing the objects in uncertain environments. The method utilizes the behavior selection network to select the most appropriate BN modules. Several experiments are performed to verify the usefulness of the proposed method.
Seung-Bin Im, Youn-Suk Song, Sung-Bae Cho
Added 23 Aug 2010
Updated 23 Aug 2010
Type Conference
Year 2006
Where FSKD
Authors Seung-Bin Im, Youn-Suk Song, Sung-Bae Cho
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