The DOI matches its Crossref record; 20 of the 20 references it cites were found in a registry or an index.
A SIFT Descriptor with Global Context
Abstract
Matching points between multiple images of a scene is a vital component of many computer vision tasks. Point matching involves creating a succinct and discriminative descriptor for each point. While current descriptors such as SIFT can find matches between features with unique local neighborhoods, these descriptors typically fail to consider global context to resolve ambiguities that can occur locally when an image has multiple similar regions. This paper presents a feature descriptor that augments SIFT with a global context vector that adds curvilinear shape information from a much larger neighborhood, thus reducing mismatches when multiple local descriptors are similar. It also provides a more robust method for handling 2D nonrigid transformations since points are more effectively matched individually at a global scale rather than constraining multiple matched points to be mapped via a planar homography. We have tested our technique on various images and compare matching accuracy between the SIFT descriptor with global context to that without.
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Cites
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A Review of Point Cloud Registration Algorithms for Mobile Robotics
Pomerleau, F., Colas, F., & Siegwart, R. (2015) · Foundations and Trends® in Robotics · doi:10.1561/2300000035 · Cited by 717
3-D Depth Reconstruction from a Single Still Image
Saxena, A., Chung, S. H., & Ng, A. Y. (2008) · International Journal of Computer Vision · doi:10.1007/s11263-007-0071-y · Cited by 600
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Ling, H., & Okada, K. (2007) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2007.1058 · Cited by 414
Effective and Efficient Global Context Verification for Image Copy Detection
Zhou, Z., Wang, Y., Wu, Q. M. J., Yang, C.-N., & Sun, X. (2017) · IEEE Transactions on Information Forensics and Security · doi:10.1109/tifs.2016.2601065 · Cited by 336
Diffusion Distance for Histogram Comparison
Ling, H., & Okada, K. (2006) · 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1 (CVPR'06) · doi:10.1109/cvpr.2006.99 · Cited by 222
Metadata
- Authors
- Mortensen, E. N., Deng, H., & Shapiro, L.
- Venue
- 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05)
- Publisher
- IEEE
- Published
- 2005-07-27
- Volume
- 1
- Pages
- 184-190
- ISSN
- 1063-6919 (ISSN-L)
- OpenAlex
- W2131213661
- Cited by
- 256
- References
- 20
- FWCI
- 8.34
- Type
- conference paper
- Language
- en
- Open access
- closed
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- Mortensen, E. N., Deng, H., & Shapiro, L. (2005). A SIFT Descriptor with Global Context. 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05). https://doi.org/10.1109/cvpr.2005.45
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