The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Comparing and evaluating interest points
Open accessAbstract
Many computer vision tasks rely on feature extraction. Interest points are such features. This paper shows that interest points are geometrically stable under different transformations and have high information content (distinctiveness). These two properties make interest points very successful in the contest of image matching. To measure these two properties quantitatively, we introduce two evaluation criteria: repeatability rate and information content. The quality of the interest points depends on the detector used. In this paper several detectors are compared according to the criteria specified above. We determine which detector gives the best results and show that it satisfies the criteria well.
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Cites
A Combined Corner and Edge Detector
Harris, C., & Stephens, M. (1988) · Procedings of the Alvey Vision Conference 1988 · doi:10.5244/c.2.23 · Cited by 12,901
Cited by
Machine Learning for High-Speed Corner Detection
Rosten, E., & Drummond, T. (2006) · Lecture Notes in Computer Science · doi:10.1007/11744023_34 · Cited by 4,555
Indexing based on scale invariant interest points
Mikolajczyk, K., & Schmid, C. (2002) · Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001 · doi:10.1109/iccv.2001.937561 · Cited by 1,101
Self-citationFast k nearest neighbor search using GPU
Garcia, V., Debreuve, E., & Barlaud, M. (2008) · 2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops · doi:10.1109/cvprw.2008.4563100 · Cited by 447
The dual-bootstrap iterative closest point algorithm with application to retinal image registration
Stewart, C. V., Tsai, C.-L., & Roysam, B. (2003) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2003.819276 · Cited by 346
Can, A., Stewart, C. V., Roysam, B., & Tanenbaum, H. L. (2002) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/34.990136 · Cited by 272
Metadata
- Authors
- Schmid, C., Mohr, R., & Bauckhage, C.
- Venue
- Sixth International Conference on Computer Vision (IEEE Cat. No.98CH36271)
- Publisher
- Narosa Publishing House
- Published
- 2002-11-27
- Pages
- 230-235
- OpenAlex
- W1773272891
- Cited by
- 265
- References
- 1
- FWCI
- 19.10
- Type
- conference paper
- Language
- en
- Open access
- green
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- Schmid, C., Mohr, R., & Bauckhage, C. (2002). Comparing and evaluating interest points. Sixth International Conference on Computer Vision (IEEE Cat. No.98CH36271). https://doi.org/10.1109/iccv.1998.710723
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