The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.
Object Recognition using Local Affine Frames on Distinguished Regions
Abstract
A novel approach to appearance based object recognition is introduced. The proposed method, based on matching of local image features, reliably recognises objects under very different viewing conditions. First, distinguished regions of data-dependent shape are robustly detected. On these regions, local affine frames are established using several affine invariant constructions. Direct comparison of photometrically normalised colour intensities in local, geometrically aligned frames results in a matching scheme that is invariant to piecewise-affine image deformations, but still remains very discriminative. The potential of the approach is experimentally verified on COIL-100 and SOIL-47 – publicly available image databases. On SOIL-47, 100 % recognition rate is achieved for single training view per object. On COIL-100, 99.9% recognition rate is obtained for 18 training views per object. Robustness to severe occlusions is demonstrated by only a moderate decrease of recognition performance in an experiment where half of each test image is erased. 1
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Cites
Distinctive Image Features from Scale-Invariant Keypoints
Lowe, D. G. (2004) · International Journal of Computer Vision · doi:10.1023/b:visi.0000029664.99615.94 · Cited by 55,589
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
Video Google: a text retrieval approach to object matching in videos
Sivic, & Zisserman (2003) · Proceedings Ninth IEEE International Conference on Computer Vision · doi:10.1109/iccv.2003.1238663 · Cited by 6,367
A comparison of affine region detectors
Mikolajczyk, K., Tuytelaars, T., Schmid, C., Zisserman, A., Matas, J., Schaffalitzky, F., Kadir, T., & Gool, L. V. (2005) · International Journal of Computer Vision · doi:10.1007/s11263-005-3848-x · Cited by 2,939
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Cited by
Video Google: a text retrieval approach to object matching in videos
Sivic, & Zisserman (2003) · Proceedings Ninth IEEE International Conference on Computer Vision · doi:10.1109/iccv.2003.1238663 · Cited by 6,367
A comparison of affine region detectors
Mikolajczyk, K., Tuytelaars, T., Schmid, C., Zisserman, A., Matas, J., Schaffalitzky, F., Kadir, T., & Gool, L. V. (2005) · International Journal of Computer Vision · doi:10.1007/s11263-005-3848-x · Cited by 2,939
Self-citationEfficient Visual Search of Videos Cast as Text Retrieval
Sivic, J., & Zisserman, A. (2009) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2008.111 · Cited by 499
Object recognition and pose estimation using color cooccurrence histograms and geometric modeling
Ekvall, S., Kragic, D., & Hoffmann, F. (2005) · Image and Vision Computing · doi:10.1016/j.imavis.2005.05.006 · Cited by 52
Metadata
- Authors
- Obdrzalek, S., & Matas, J.
- Venue
- Procedings of the British Machine Vision Conference 2002
- Publisher
- British Machine Vision Association
- Published
- 2002
- Pages
- 9.1-9.10
- OpenAlex
- W2157788957
- Cited by
- 198
- References
- 4
- FWCI
- 7.84
- Type
- conference paper
- Language
- en
- Open access
- closed
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- Obdrzalek, S., & Matas, J. (2002). Object Recognition using Local Affine Frames on Distinguished Regions. Procedings of the British Machine Vision Conference 2002. https://doi.org/10.5244/c.16.9
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