Publication

Keypoint Signatures for Fast Learning and Recognition

Pascal Fua, Vincent Lepetit, Michael Calonder
2008
Conference Papers

Abstract

Statistical learning techniques have been used to dramatically speed-up keypoint matching by training a classifier to recognize a specific set of keypoints. However, the training itself is usually relatively slow and performed offline. Although methods have recently been proposed to train the classifier online, they can only learn a very limited number of new keypoints. This represents a handicap for real-time applications, such as Simultaneous Localization and Mapping (SLAM), which require incremental addition of arbitrary numbers of keypoints as they become visible.

Official source

https://infoscience.epfl.ch/entities/publication/4d251937-3ca3-4e71-b551-7eb25853c3f0

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Pascal Fua, Vincent Lepetit, Michael Calonder
2008
Conference Papers

Abstract

Official source

https://infoscience.epfl.ch/entities/publication/4d251937-3ca3-4e71-b551-7eb25853c3f0

About this result

Related concepts (24)

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In computer science, online machine learning is a method of machine learning in which data becomes available in a sequential order and is used to update the best predictor for future data at each step, as opposed to batch learning techniques which generate the best predictor by learning on the entire training data set at once. Online learning is a common technique used in areas of machine learning where it is computationally infeasible to train over the entire dataset, requiring the need of out-of-core algorithms.

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