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Proceedings Paper

Image categorization based on spatial visual vocabulary model
Author(s): Yuxin Wang; Changqin He; He Guo; Zhen Feng; Qi Jia
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Paper Abstract

In this paper, we propose an approach to recognize scene categories by means of a novel method named spatial visual vocabulary. Firstly, we hierarchically divide images into sub regions and construct the spatial visual vocabulary by grouping the low-level features collected from every corresponding spatial sub region into a specified number of clusters using k-means algorithm. To recognize the category of a scene, the visual vocabulary distributions of all spatial sub regions are concatenated to form a global feature vector. The classification is obtained using LIBSVM, a support vector machine classifier. Our goal is to find a universal framework which is applicable to various types of features, so two kinds of features are used in the experiments: "V1-like" filters and PACT features. In almost all experimental cases, the proposed model achieves superior results. Source codes are available by email.

Paper Details

Date Published: 20 August 2010
PDF: 8 pages
Proc. SPIE 7820, International Conference on Image Processing and Pattern Recognition in Industrial Engineering, 78202P (20 August 2010); doi: 10.1117/12.867045
Show Author Affiliations
Yuxin Wang, Dalian Univ. of Technology (China)
Changqin He, Dalian Univ. of Technology (China)
He Guo, Dalian Univ. of Technology (China)
Zhen Feng, Dalian Univ. of Technology (China)
Qi Jia, Dalian Univ. of Technology (China)


Published in SPIE Proceedings Vol. 7820:
International Conference on Image Processing and Pattern Recognition in Industrial Engineering
Shaofei Wu; Zhengyu Du; Shaofei Wu; Zhengyu Du; Shaofei Wu; Zhengyu Du, Editor(s)

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