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Updated: Dec 29, 2025

Methods for Presenting Real-world Objects Under Controlled Laboratory Conditions
Published on: June 21, 2019
Online learning of objects in a biologically motivated visual architecture
Heiko Wersing1, Stephan Kirstein, Michael Götting
1Honda Research Institute Europe GmbH, Carl-Legien-Street 30, 63073 Offenbach/Main, Germany. heiko.wersing@honda-ri.de
Abstract:
We present a biologically motivated architecture for object recognition that is capable of online learning of several objects based on interaction with a human teacher. The system combines biological principles such as appearance-based representation in topographical feature detection hierarchies and context-driven transfer between different levels of object memory. Training can be performed in an unconstrained environment by presenting objects in front of a stereo camera system and labeling them by speech input. The learning is fully online and thus avoids an artificial separation of the interaction into training and test phases. We demonstrate the performance on a challenging ensemble of 50 objects.
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