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FSKD
2006
Springer
122views Fuzzy Logic» more  FSKD 2006»
13 years 11 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 s...
Seung-Bin Im, Youn-Suk Song, Sung-Bae Cho
ACIVS
2006
Springer
13 years 11 months ago
Context-Based Scene Recognition Using Bayesian Networks with Scale-Invariant Feature Transform
Scene understanding is an important problem in intelligent robotics. Since visual information is uncertain due to several reasons, we need a novel method that has robustness to the...
Seung-Bin Im, Sung-Bae Cho
KES
2005
Springer
14 years 1 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 geometri...
Youn-Suk Song, Sung-Bae Cho, Il Hong Suh
FGCN
2008
IEEE
175views Communications» more  FGCN 2008»
14 years 2 months ago
Environment Recognition Based on Human Actions Using Probability Networks
To realize context aware applications for smart home environments, it is necessary to recognize function or usage of objects as well as categories of them. On conventional researc...
Hiroshi Miki, Atsuhiro Kojima, Koichi Kise
ROMAN
2007
IEEE
179views Robotics» more  ROMAN 2007»
14 years 2 months ago
A Bayesian Network Framework for Vision Based Semantic Scene Understanding
— For a robot to understand a scene, we have to infer and extract meaningful information from vision sensor data. Since scene understanding consists in recognizing several visual...
Seung-Bin Im, Keum-Sung Hwang, Sung-Bae Clio