Cited By
View all- Qu YWu SLiu HXie YWang H(2018)Evaluation of local features and classifiers in BOW model for image classificationMultimedia Tools and Applications10.1007/s11042-012-1107-z70:2(605-624)Online publication date: 31-Dec-2018
Optimal operations for visual categorization
Pages 73 - 76
Abstract
Bag-of-words is the state-of-the-art method used in visual categorization. The performance of visual categorization depends on four main operations: the detection of interest point, the description of interest point, the design of classifier, and the construction of codebook. In this paper, we focus on the optimizations of the first three operations. Firstly, we compare several popular detectors of interest points and propose an optimal detector combined MSER detector with Hessian-Laplace detector to sample the key points. This detector well combines the interest region with the interest point such that the image can be represented in a hierarchical way. Secondly, we adopt SIFT to describe the sampling region because our experiment results demonstrate that SIFT is more robust than other popular descriptors. Thirdly, we use SVM with RBF kernel for object classification. The proposed classifier outperforms other classifier in terms of the classification accuracy. In order to verify three proposed optimal operations, we implement them in two image datasets: Caltech and KTH-TIPS. The experimental results show that our optimal operations can increase the accuracy of object categorization.
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- Optimal operations for visual categorization
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Published In
December 2010
218 pages
ISBN:9781450304603
DOI:10.1145/1937728
- General Chairs:
- Yong Rui,
- Klara Nahrstedt,
- Xiaofei Xu,
- Program Chairs:
- Hongxun Yao,
- Shuqiang Jiang,
- Jian Cheng
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Published: 30 December 2010
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ICIMCS '10
ICIMCS '10: The Second International Conference on Internet Multimedia Computing and Service
December 30 - 31, 2010
Harbin, China
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Overall Acceptance Rate 163 of 456 submissions, 36%
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View all- Qu YWu SLiu HXie YWang H(2018)Evaluation of local features and classifiers in BOW model for image classificationMultimedia Tools and Applications10.1007/s11042-012-1107-z70:2(605-624)Online publication date: 31-Dec-2018
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