TY - GEN
T1 - Objects relationship modeling for improving object detection using bayesian network integration
AU - Song, Youn Suk
AU - Cho, Sung Bae
PY - 2006
Y1 - 2006
N2 - Object detection is very important to service robots. Many tasks for service such as delivery, cleaning, and health-care for elderly people are strongly related to objects. Conventional approaches for object detection are mainly based on the geometric models, because they have been applied to static environments. In indoor environments having uncertainty, they have limitation in some situations where interesting objects are occluded by other ones or small in the scene. Context information can be helpful to overcome these uncertain situations. In this paper, we adopt objects as context information to allow for service robots to predict the probability of interesting objects through observed ones. For this, an object relationship model based on Bayesian network (BN) and integration method are proposed. Experimental results confirm that the proposed method predicts the objects very well.
AB - Object detection is very important to service robots. Many tasks for service such as delivery, cleaning, and health-care for elderly people are strongly related to objects. Conventional approaches for object detection are mainly based on the geometric models, because they have been applied to static environments. In indoor environments having uncertainty, they have limitation in some situations where interesting objects are occluded by other ones or small in the scene. Context information can be helpful to overcome these uncertain situations. In this paper, we adopt objects as context information to allow for service robots to predict the probability of interesting objects through observed ones. For this, an object relationship model based on Bayesian network (BN) and integration method are proposed. Experimental results confirm that the proposed method predicts the objects very well.
UR - http://www.scopus.com/inward/record.url?scp=33749574812&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=33749574812&partnerID=8YFLogxK
U2 - 10.1007/11816157_126
DO - 10.1007/11816157_126
M3 - Conference contribution
AN - SCOPUS:33749574812
SN - 3540372717
SN - 9783540372714
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 1040
EP - 1046
BT - International Conference on Intelligent Computing, ICIC 2006, Proceedings
PB - Springer Verlag
T2 - International Conference on Intelligent Computing, ICIC 2006
Y2 - 16 August 2006 through 19 August 2006
ER -