Image categorization based on visual saliency and Bag-of-Words model

Wenxiang Li; Yanfei Chen; Zechang Wu; Hongsheng Peng

doi:10.1117/12.2538139

14 February 2020 Image categorization based on visual saliency and Bag-of-Words model

Wenxiang Li, Yanfei Chen, Zechang Wu, Hongsheng Peng

Proceedings Volume 11430, MIPPR 2019: Pattern Recognition and Computer Vision; 114300M (2020) https://doi.org/10.1117/12.2538139
Event: Eleventh International Symposium on Multispectral Image Processing and Pattern Recognition (MIPPR2019), 2019, Wuhan, China

Abstract

Large-scale image categorization is a challenging task. In this paper, we propose a new image categorization approach based on visual saliency and bag-of-words model. Firstly, a saliency map is generated by visual saliency method that exploits some coarsely localized information, i.e. the salient region shape and contour. Secondly, size of salient region is acquired by calculating maximum entropy. Thirdly, the local image descriptor-SIFT extracted in the salient region and visual saliency information are combined to build visual words. Finally, the visual word bag is categorized by Support Vector Machine. By comparing with BOW model categorization methods, experiment results show that our methods can effectively improve the accuracy of image categorization.

Citation Download Citation

Wenxiang Li, Yanfei Chen, Zechang Wu, and Hongsheng Peng "Image categorization based on visual saliency and Bag-of-Words model", Proc. SPIE 11430, MIPPR 2019: Pattern Recognition and Computer Vision, 114300M (14 February 2020); https://doi.org/10.1117/12.2538139

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KEYWORDS

Visualization

Information visualization

Visual process modeling

Feature extraction

Databases

Digital imaging

Image retrieval

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