A Bayesian network approach to natural scene classification

Huanhuan Cheng; Runsheng Wang

doi:10.1117/12.833417

30 October 2009 A Bayesian network approach to natural scene classification

Huanhuan Cheng, Runsheng Wang

Proceedings Volume 7495, MIPPR 2009: Automatic Target Recognition and Image Analysis; 749504 (2009) https://doi.org/10.1117/12.833417
Event: Sixth International Symposium on Multispectral Image Processing and Pattern Recognition, 2009, Yichang, China

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.

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Huanhuan Cheng and Runsheng Wang "A Bayesian network approach to natural scene classification", Proc. SPIE 7495, MIPPR 2009: Automatic Target Recognition and Image Analysis, 749504 (30 October 2009); https://doi.org/10.1117/12.833417

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KEYWORDS

Scene classification

Image segmentation

Image processing

Classification systems

Databases

Coastal modeling

Feature extraction

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