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Authors: Pramod Chandrashekhariah ; Gabriele Spina and Jochen Triesch

Affiliation: Johann Wolfgang Goethe University, Germany

ISBN: 978-989-8565-48-8

Keyword(s): Active Vision, Unsupervised Learning, Autonomous Vision System, Vision for Robotics, Humanoid Robot, iCub, Object Recognition, Visual Attention, Stereo Vision, Intrinsic Motivation.

Related Ontology Subjects/Areas/Topics: Active and Robot Vision ; Computer Vision, Visualization and Computer Graphics ; Early and Biologically-Inspired Vision ; Image and Video Analysis ; Motion, Tracking and Stereo Vision ; Visual Attention and Image Saliency

Abstract: We present a “curious” active vision system for a humanoid robot that autonomously explores its environment and learns object representations without any human assistance. Similar to an infant, who is intrinsically motivated to seek out new information, our system is endowed with an attention and learning mechanism designed to search for new information that has not been learned yet. Our method can deal with dynamic changes of object appearance which are incorporated into the object models. Our experiments demonstrate improved learning speed and accuracy through curiosity-driven learning.

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Paper citation in several formats:
Chandrashekhariah, P.; Spina, G. and Triesch, J. (2013). Let it Learn - A Curious Vision System for Autonomous Object Learning.In Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2013) ISBN 978-989-8565-48-8, pages 169-176. DOI: 10.5220/0004294101690176

@conference{visapp13,
author={Pramod Chandrashekhariah. and Gabriele Spina. and Jochen Triesch.},
title={Let it Learn - A Curious Vision System for Autonomous Object Learning},
booktitle={Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2013)},
year={2013},
pages={169-176},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004294101690176},
isbn={978-989-8565-48-8},
}

TY - CONF

JO - Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2013)
TI - Let it Learn - A Curious Vision System for Autonomous Object Learning
SN - 978-989-8565-48-8
AU - Chandrashekhariah, P.
AU - Spina, G.
AU - Triesch, J.
PY - 2013
SP - 169
EP - 176
DO - 10.5220/0004294101690176

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