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Journal of Electronic Imaging

Cognition inspired framework for indoor scene annotation
Author(s): Zhipeng Ye; Peng Liu; Wei Zhao; Xianglong Tang
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Paper Abstract

We present a simple yet effective scene annotation framework based on a combination of bag-of-visual words (BoVW), three-dimensional scene structure estimation, scene context, and cognitive theory. From a macroperspective, the proposed cognition-based hybrid motivation framework divides the annotation problem into empirical inference and real-time classification. Inspired by the inference ability of human beings, common objects of indoor scenes are defined for experience-based inference, while in the real-time classification stage, an improved BoVW-based multilayer abstract semantics labeling method is proposed by introducing abstract semantic hierarchies to narrow the semantic gap and improve the performance of object categorization. The proposed framework was evaluated on a variety of common data sets and experimental results proved its effectiveness.

Paper Details

Date Published: 21 September 2015
PDF: 11 pages
J. Electron. Imaging. 24(5) 053013 doi: 10.1117/1.JEI.24.5.053013
Published in: Journal of Electronic Imaging Volume 24, Issue 5
Show Author Affiliations
Zhipeng Ye, Harbin Institute of Technology (China)
Peng Liu, Harbin Institute of Technology (China)
Wei Zhao, Harbin Institute of Technology (China)
Xianglong Tang, Harbin Institute of Technology (China)


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