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Proceedings Paper

A Bayesian network approach to natural scene classification
Author(s): Huanhuan Cheng; Runsheng Wang
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Paper Abstract

This paper presents a novel approach using a context-sensitive Bayesian network for natural scene modeling and classification. In contrast to the common approach using of semantic features, we learn the major spatial arrangement (spatial and context information) of scenes and relationships between local semantic concepts and global scene meanings using a contextual Bayesian network. Images' scene probabilities are inferred in a two-level process based on characteristic objects in the image as well as spatial arrangements of key entities through the Bayesian network. We demonstrate the promise of this Bayesian network approach on a set of natural scenes, comparing it with existing state of art approaches.

Paper Details

Date Published: 30 October 2009
PDF: 7 pages
Proc. SPIE 7495, MIPPR 2009: Automatic Target Recognition and Image Analysis, 749504 (30 October 2009); doi: 10.1117/12.833417
Show Author Affiliations
Huanhuan Cheng, National Univ. of Defense Technology (China)
Runsheng Wang, National Univ. of Defense Technology (China)


Published in SPIE Proceedings Vol. 7495:
MIPPR 2009: Automatic Target Recognition and Image Analysis
Tianxu Zhang; Bruce Hirsch; Zhiguo Cao; Hanqing Lu, Editor(s)

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