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Journal of Electronic Imaging • new

Hierarchy-associated semantic-rule inference framework for classifying indoor scenes
Author(s): Dan Yu; Peng Liu; Zhipeng Ye; Xianglong Tang; Wei Zhao
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Paper Abstract

Typically, the initial task of classifying indoor scenes is challenging, because the spatial layout and decoration of a scene can vary considerably. Recent efforts at classifying object relationships commonly depend on the results of scene annotation and predefined rules, making classification inflexible. Furthermore, annotation results are easily affected by external factors. Inspired by human cognition, a scene-classification framework was proposed using the empirically based annotation (EBA) and a match-over rule-based (MRB) inference system. The semantic hierarchy of images is exploited by EBA to construct rules empirically for MRB classification. The problem of scene classification is divided into low-level annotation and high-level inference from a macro perspective. Low-level annotation involves detecting the semantic hierarchy and annotating the scene with a deformable-parts model and a bag-of-visual-words model. In high-level inference, hierarchical rules are extracted to train the decision tree for classification. The categories of testing samples are generated from the parts to the whole. Compared with traditional classification strategies, the proposed semantic hierarchy and corresponding rules reduce the effect of a variable background and improve the classification performance. The proposed framework was evaluated on a popular indoor scene dataset, and the experimental results demonstrate its effectiveness.

Paper Details

Date Published: 28 March 2016
PDF: 16 pages
J. Electron. Imaging. 25(2) 023008 doi: 10.1117/1.JEI.25.2.023008
Published in: Journal of Electronic Imaging Volume 25, Issue 2
Show Author Affiliations
Dan Yu, Harbin Institute of Technology (China)
Peng Liu, Harbin Institute of Technology (China)
Zhipeng Ye, Harbin Institute of Technology (China)
Xianglong Tang, Harbin Institute of Technology (China)
Wei Zhao, Harbin Institute of Technology (China)


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