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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Zhu Songhao Zou Liming Liang Zhiwei Fan Lili |
| Copyright Year | 2012 |
| Description | Author affiliation: School of Automation, Nanjing University of Post and Telecommunications, Nanjing, 210046 (Zhu Songhao; Zou Liming; Liang Zhiwei) || Nanjing Research and Development Center, Motorola Mobile Technology Limited Company (Fan Lili) |
| Abstract | Nowadays tag-based image search on image retrieval systems like Flickr, Google does not provide the option of relevance-based ranking. In this paper, a relevance-based ranking scheme which integrates both the visual features and the semantic annotations is proposed. The semantic correlation between database images and input tags is described using an improved form of Google distance, and the visual consistency between images is computed with Gaussian function. Experimental results demonstrate that the proposed approach taking into account the visual features and semantic annotations helps to improve the retrieval performance significantly. |
| Starting Page | 3964 |
| Ending Page | 3968 |
| File Size | 305225 |
| Page Count | 5 |
| File Format | |
| ISBN | 9781467325813 |
| ISSN | 21612927 |
| e-ISBN | 9789881563811 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2012-07-25 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Chinese Assoc of Automati |
| Subject Keyword | visual feature Visualization Google Computer vision Conferences Image retrieval Semantics semantic annotation relevance ranking Electronic mail |
| Content Type | Text |
| Resource Type | Article |
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