TY - GEN
T1 - Context-based scene recognition using bayesian networks with scale-invariant feature transform
AU - Im, Seung Bin
AU - Cho, Sung Bae
N1 - Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.
PY - 2006
Y1 - 2006
N2 - 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 uncertainty. Bayesian probabilistic approach is robust to manage the uncertainty, and powerful to model high-level contexts like the relationship between places and objects. In this paper, we propose a context-based Bayesian method with SIFT for scene understanding. At first, image pre-processing extracts features from vision information and objectsexistence information is extracted by SIFT that is rotation and scale invariant. This information is provided to Bayesian networks for robust inference in scene understanding. Experiments in complex real environments show that the proposed method is useful.
AB - 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 uncertainty. Bayesian probabilistic approach is robust to manage the uncertainty, and powerful to model high-level contexts like the relationship between places and objects. In this paper, we propose a context-based Bayesian method with SIFT for scene understanding. At first, image pre-processing extracts features from vision information and objectsexistence information is extracted by SIFT that is rotation and scale invariant. This information is provided to Bayesian networks for robust inference in scene understanding. Experiments in complex real environments show that the proposed method is useful.
UR - http://www.scopus.com/inward/record.url?scp=33750266379&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=33750266379&partnerID=8YFLogxK
U2 - 10.1007/11864349_98
DO - 10.1007/11864349_98
M3 - Conference contribution
AN - SCOPUS:33750266379
SN - 3540446303
SN - 9783540446309
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 1080
EP - 1087
BT - Advanced Concepts for Intelligent Vision Systems - 8th International Conference, ACIVS 2006, Proceedings
PB - Springer Verlag
T2 - 8th International Conference on Advanced Concepts for Intelligent Vision Systems, ACIVS 2006
Y2 - 18 September 2006 through 21 September 2006
ER -