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Scenes and Tracking with Dynamic Neural Fields: How to Update a Robotic Scene Representation

  • We present an architecture based on the Dynamic Field Theory for the problem of scene representation. At the core of this architecture are three-dimensional neural fields linking feature to spatial information. These three-dimensional fields are coupled to lower-dimensional fields that provide both a close link to the sensory surface and a close link to motor behavior. We highlight the updating mechanism of this architecture, both when a single object is selected and followed by the robot's head in smooth pursuit and in multi-item tracking when several items move simultaneously

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Metadaten
Author:Stephan K.U. Zibner, Christian Faubel, Ioannis Iossifidis, Gregor Schöner, John P. Spencer
URL:https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=5578837
DOI:https://doi.org/10.1109/DEVLRN.2010.5578837
ISBN:978-1-4244-6902-4
ISSN:2161-9476
Parent Title (German):IEEE 9TH International Conference on Development and Learning
Publisher:IEEE
Place of publication:Ann Arbor, MI, USA
Document Type:Conference Proceeding
Language:English
Year of Completion:2010
Release Date:2019/04/12
First Page:244
Last Page:250
Note:
Zugriff aus dem Hochschulnetz der Hochschule Ruhr West
Institutes:Fachbereich 1 - Institut Informatik
DDC class:000 Allgemeines, Informatik, Informationswissenschaft / 004 Informatik
Licence (German):License LogoNo Creative Commons