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| Content Provider | ACM Digital Library |
|---|---|
| Author | Yin, Guangxue An, Lingling Gao, Xinbo |
| Abstract | In recent years, graph matching has attracted much attention to solve computer vision problems, such as image re-ranking and object recognition. However, graph matching algorithms, e.g., reweighted random walks, cannot be properly applied for near-duplicated image retrieval (NDIR) due to the ignorance of duplicated patches in images. Therefore, this paper proposes a novel graph matching with geometric constraints for NDIR, which explores the spatial relationships in image patches and introduces geometric constraints to remove the false matches, leading to good retrieval results for NDIR. Empirical studies on duplicated ground truth datasets suggest the effectiveness of the proposed approach. |
| Starting Page | 174 |
| Ending Page | 177 |
| Page Count | 4 |
| File Format | |
| ISBN | 9781450322522 |
| DOI | 10.1145/2499788.2499847 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2013-08-17 |
| Publisher Place | New York |
| Access Restriction | Subscribed |
| Subject Keyword | Near-duplicated image retrieval Geometric constraints Graph matching |
| Content Type | Text |
| Resource Type | Article |
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