The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Randomized Trees for Real-Time Keypoint Recognition
Open accessAbstract
In earlier work, we proposed treating wide baseline matching of feature points as a classification problem, in which each class corresponds to the set of all possible views of such a point. We used a K-mean plus Nearest Neighbor classifier to validate our approach, mostly because it was simple to implement. It has proved effective but still too slow for real-time use. In this paper, we advocate instead the use of randomized trees as the classification technique. It is both fast enough for real-time performance and more robust. It also gives us a principled way not only to match keypoints but to select during a training phase those that are the most recognizable ones. This results in a real-time system able to detect and position in 3D planar, non-planar, and even deformable objects. It is robust to illuminations changes, scale changes and occlusions.
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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
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Self-citationFast Discriminative Visual Codebooks using Randomized Clustering Forests
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Huang, S. H., Pan, J., Mulcaire, G., & Abbeel, P. (2015) · 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) · doi:10.1109/iros.2015.7353475 · Cited by 39
Metadata
- Authors
- Lepetit, V., Lagger, P., & Fua, P.
- Venue
- 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05)
- Publisher
- IEEE
- Published
- 2005-07-27
- Volume
- 2
- Pages
- 775-781
- ISSN
- 1063-6919 (ISSN-L)
- OpenAlex
- W2131296063
- Cited by
- 415
- References
- 2
- FWCI
- 20.84
- Type
- conference paper
- Language
- en
- Open access
- green
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