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Conference Paper
Multi-stage Image Retrieval based on Feature Augmentation with Truncated Polynomial Weight
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- Authors
- Keundong Lee, Seungjae Lee, Wonyoung Yoo
- Issue Date
- 2018-10
- Citation
- International Conference on Information and Communication Technology Convergence (ICTC) 2018, pp.480-483
- Publisher
- IEEE
- Language
- English
- Type
- Conference Paper
- Abstract
- In this paper, we propose an effective image retrieval method. Based on a conventional global image representation, multi-stage image retrieval pipeline with feature augmentation is constructed to improve retrieval accuracy. To suppress irrelevant images while boosting relevant images, a novel weighting scheme for feature augmentation is introduced. In addition, the relationship between database images is leveraged to update or re-rank shortlist of the retrieved images. The proposed method was evaluated on Google-landmarks dataset, and the experimental results validate the effectiveness of the proposed method.
- KSP Keywords
- Feature augmentation, Image Representation, Image retrieval, Multi-stage, Re-rank, Weighting scheme, retrieval accuracy, retrieval method