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

Test Sequences

Original frames (259Mb !).

Relevant Publications

M. Calonder, V. Lepetit, P. Fua, K. Konolige, J. Bowman, and P. Mihelich, Compact Signatures for High-speed Interest Point Description and Matching. In Proceedings of the International Conference on Computer Vision, 2009.

M. Calonder, V. Lepetit, P. Fua, Keypoint Signatures for Fast Learning and Recognition, European Conference on Computer Vision, Marseille, France, 2008.

M. Ozuysal, M. Calonder, V. Lepetit, and P. Fua, Fast Keypoint Recognition using Random Ferns. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2010.

V. Lepetit and P. Fua, Keypoint Recognition using Randomized Trees. IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 28, Nr. 9, pp. 1465-1479, 2006.