Randomized Trees and Ferns: Keypoint Matching by Classification

Before BRIEF, we developed a fast method for keypoint recognition based on classification. We first used Randomized Trees as the classifier, and then developed the Ferns, a simplified version relying on a Naive Bayesian approach for better performances.

Videos


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Test Sequences

Original frames (259Mb !).

Relevant Publications

Compact Signatures for High-speed Interest Point Description and Matching

M. Calonder; V. Lepetit; P. Fua; K. Konolige; J. Bowman et al. 

2009. IEEE International Conference on Computer Vision, Kyoto, JAPAN, Sep 29-Oct 02, 2009. p. 357-364. DOI : 10.1109/ICCV.2009.5459272.

Keypoint Signatures for Fast Learning and Recognition

M. Calonder; V. Lepetit; P. Fua 

2008. European Conference on Computer Vision, Marseille, FRANCE, Oct 12-18, 2008. p. 58-71. DOI : 10.1007/978-3-540-88682-2_6.

Keypoint Signatures for Fast Learning and Recognition

M. Calonder; V. Lepetit; P. Fua 

2008. European Conference on Computer Vision, Marseilles, October 2008. p. 58-71. DOI : 10.1007/978-3-540-88682-2_6.

Fast Keypoint Recognition using Random Ferns

M. Özuysal; M. Calonder; V. Lepetit; P. Fua 

IEEE Transactions on Pattern Analysis and Machine Intelligence. 2010. Vol. 32, num. 3, p. 448-461. DOI : 10.1109/TPAMI.2009.23.

Keypoint Recognition using Randomized Trees

V. Lepetit; P. Fua 

IEEE Transactions on Pattern Analysis and Machine Intelligence. 2006. Vol. 28, num. 9, p. 1465-1479. DOI : 10.1109/TPAMI.2006.188.