Context-based scene recognition using bayesian networks with scale-invariant feature transform

Seung Bin Im; Sung Bae Cho

doi:10.1007/11864349_98

Context-based scene recognition using bayesian networks with scale-invariant feature transform

Seung Bin Im, Sung Bae Cho

Department of Computer Science

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

11 Citations (Scopus)

Abstract

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.

Original language	English
Title of host publication	Advanced Concepts for Intelligent Vision Systems - 8th International Conference, ACIVS 2006, Proceedings
Publisher	Springer Verlag
Pages	1080-1087
Number of pages	8
ISBN (Print)	3540446303, 9783540446309
DOIs	https://doi.org/10.1007/11864349_98
Publication status	Published - 2006
Event	8th International Conference on Advanced Concepts for Intelligent Vision Systems, ACIVS 2006 - Antwerp, Belgium Duration: 2006 Sep 18 → 2006 Sep 21

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	4179 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Other

Other	8th International Conference on Advanced Concepts for Intelligent Vision Systems, ACIVS 2006
Country	Belgium
City	Antwerp
Period	06/9/18 → 06/9/21

All Science Journal Classification (ASJC) codes

Theoretical Computer Science
Computer Science(all)

Access to Document

10.1007/11864349_98

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Im, S. B., & Cho, S. B. (2006). Context-based scene recognition using bayesian networks with scale-invariant feature transform. In Advanced Concepts for Intelligent Vision Systems - 8th International Conference, ACIVS 2006, Proceedings (pp. 1080-1087). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4179 LNCS). Springer Verlag. https://doi.org/10.1007/11864349_98

Im, Seung Bin ; Cho, Sung Bae. / Context-based scene recognition using bayesian networks with scale-invariant feature transform. Advanced Concepts for Intelligent Vision Systems - 8th International Conference, ACIVS 2006, Proceedings. Springer Verlag, 2006. pp. 1080-1087 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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abstract = "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.",

author = "Im, {Seung Bin} and Cho, {Sung Bae}",

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Im, SB & Cho, SB 2006, Context-based scene recognition using bayesian networks with scale-invariant feature transform. in Advanced Concepts for Intelligent Vision Systems - 8th International Conference, ACIVS 2006, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 4179 LNCS, Springer Verlag, pp. 1080-1087, 8th International Conference on Advanced Concepts for Intelligent Vision Systems, ACIVS 2006, Antwerp, Belgium, 06/9/18. https://doi.org/10.1007/11864349_98

Context-based scene recognition using bayesian networks with scale-invariant feature transform. / Im, Seung Bin; Cho, Sung Bae.

Advanced Concepts for Intelligent Vision Systems - 8th International Conference, ACIVS 2006, Proceedings. Springer Verlag, 2006. p. 1080-1087 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4179 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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Im SB, Cho SB. Context-based scene recognition using bayesian networks with scale-invariant feature transform. In Advanced Concepts for Intelligent Vision Systems - 8th International Conference, ACIVS 2006, Proceedings. Springer Verlag. 2006. p. 1080-1087. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/11864349_98