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Cognition inspired framework for indoor scene annotation

[+] Author Affiliations
Zhipeng Ye, Peng Liu, Wei Zhao, Xianglong Tang

Harbin Institute of Technology, Pattern Recognition and Intelligent System Research Center, School of Computer Science and Technology, 92 West Dazhi Street, Harbin 150001, China

J. Electron. Imaging. 24(5), 053013 (Sep 21, 2015). doi:10.1117/1.JEI.24.5.053013
History: Received April 6, 2015; Accepted August 20, 2015
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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.

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Citation

Zhipeng Ye ; Peng Liu ; Wei Zhao and Xianglong Tang
"Cognition inspired framework for indoor scene annotation", J. Electron. Imaging. 24(5), 053013 (Sep 21, 2015). ; http://dx.doi.org/10.1117/1.JEI.24.5.053013


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