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Erschienen in:
2006 | OriginalPaper | Buchkapitel
A Biologically Motivated System for Unconstrained Online Learning of Visual Objects
verfasst von : Heiko Wersing, Stephan Kirstein, Michael Götting, Holger Brandl, Mark Dunn, Inna Mikhailova, Christian Goerick, Jochen Steil, Helge Ritter, Edgar Körner
Erschienen in: Artificial Neural Networks – ICANN 2006
Verlag: Springer Berlin Heidelberg
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We present a biologically motivated system for object recognition that is capable of online learning of several objects based on interaction with a human teacher. The training is unconstrained in the sense that arbitrary objects can be freely presented in front of a stereo camera system and labeled by speech input. The architecture unites biological principles such as appearance-based representation in topographical feature detection hierarchies and context-driven transfer between different levels of object memory. The learning is fully online and thus avoids an artificial separation of the interaction into training and test phases.