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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Wenjie Xie De Xu Songhe Feng Yingjun Tang |
| Copyright Year | 2010 |
| Description | Author affiliation: Institute of Computer Science and Engineering, Beijing Jiaotong University, Beijing, China (Wenjie Xie; De Xu; Songhe Feng; Yingjun Tang) |
| Abstract | In scene categorization, one single histogram based on the sole universal codebook is used to characterize an image in most state-of-the-art scene categorization methods, which is lack of enough discriminative ability to separate the images among different categories and results in low classification accuracy. In order to solve the problem, in this paper, we propose a novel scene categorization approach that constructs class-specific codebooks based on feature selection method. In our proposed approach, feature selection method is adopted to measure the visual word's contribution and construct class-specific codebook for each category. Then, an image is characterized by a set of combined histograms (one histogram per class) which are generated by concentrating the traditional histogram based on universal codebook and the class-specific histogram grounded on class-specific codebook with an adaptive weighting coefficient. The improved combined-histogram provides useful information or cue to overcome the similarity of inter-class images. Experimental results on Lazebnik 15 dataset show that our proposed scene categorization method significantly outperforms the state-of-the-art approaches. |
| Starting Page | 948 |
| Ending Page | 951 |
| File Size | 146762 |
| Page Count | 4 |
| File Format | |
| ISBN | 9781424458974 |
| e-ISBN | 9781424459001 |
| DOI | 10.1109/ICOSP.2010.5655717 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2010-10-24 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Histograms Visualization Accuracy Semantics Feature extraction Support vector machines Computer vision specific-class codebook scene categorization feature selection combined histogram |
| Content Type | Text |
| Resource Type | Article |
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