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GMS: Grid-Based Motion Statistics for Fast, Ultra-Robust Feature Correspondence
Open accessAbstract
Incorporating smoothness constraints into feature matching is known to enable ultra-robust matching. However, such formulations are both complex and slow, making them unsuitable for video applications. This paper proposes GMS (Grid-based Motion Statistics), a simple means of encapsulating motion smoothness as the statistical likelihood of a certain number of matches in a region. GMS enables translation of high match numbers into high match quality. This provides a real-time, ultra-robust correspondence system. Evaluation on videos, with low textures, blurs and wide-baselines show GMS consistently out-performs other real-time matchers and can achieve parity with more sophisticated, much slower techniques.
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Metadata
- Authors
- Bian, J., Lin, W.-Y., Matsushita, Y., Yeung, S.-K., Nguyen, T.-D., & Cheng, M.-M.
- Venue
- 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
- Publisher
- IEEE
- Published
- 2017-07
- Pages
- 2828-2837
- ISSN
- 1063-6919 (ISSN-L)
- OpenAlex
- W2754925132
- Cited by
- 594
- References
- 45
- FWCI
- 14.16
- Type
- conference paper
- Language
- en
- Open access
- green
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