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Authors: Husam Al-Behadili 1 ; Arne Grumpe 2 and Christian Wöhler 2

Affiliations: 1 University of Mustansiriyah and TU Dortmund University, Iraq ; 2 TU Dortmund University, Germany

ISBN: 978-989-758-175-5

Keyword(s): Data Stream, Neural Network, Extreme learning Machine (ELM), Novelty Detection, Incremental Learning, Semi-supervised Learning, Extreme Value Theory (EVT), Confidence Band.

Related Ontology Subjects/Areas/Topics: Applications and Services ; Computer Vision, Visualization and Computer Graphics ; Enterprise Information Systems ; Human and Computer Interaction ; Human-Computer Interaction

Abstract: The problems of infinitely long data streams and its concept drift as well as non-linearly separable classes and the possible emergence of “novel classes” are topics of high relevance for gesture data streaming based automatic recognition systems. To address these problems we apply a semi-supervised learning technique using a neural network in combination with an incremental update rule. Neural networks have been shown to handle non-linearly separable data and the incremental update ensures that the parameters of the classifier follow the “concept-drift” without the necessity of an increased training set. Since a semi-supervised learning technique is sensitive to false labels, we apply an outlier detection method based on extreme value theory and confidence band intervals. The proposed algorithm uses the extreme learning machine, which is easily updated and works with multi-classes. A comparison with an auto-encoder neural network shows that the proposed algorithm has superior propert ies. Especially, the processing time is greatly reduced. (More)

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Paper citation in several formats:
Al-Behadili, H.; Grumpe, A. and Wöhler, C. (2016). Neural Network based Novelty Detection for Incremental Semi-supervised Learning in Multi-class Gesture Recognition.In Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: VISAPP, (VISIGRAPP 2016) ISBN 978-989-758-175-5, pages 287-294. DOI: 10.5220/0005674202870294

@conference{visapp16,
author={Husam Al{-}Behadili. and Arne Grumpe. and Christian Wöhler.},
title={Neural Network based Novelty Detection for Incremental Semi-supervised Learning in Multi-class Gesture Recognition},
booktitle={Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: VISAPP, (VISIGRAPP 2016)},
year={2016},
pages={287-294},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005674202870294},
isbn={978-989-758-175-5},
}

TY - CONF

JO - Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: VISAPP, (VISIGRAPP 2016)
TI - Neural Network based Novelty Detection for Incremental Semi-supervised Learning in Multi-class Gesture Recognition
SN - 978-989-758-175-5
AU - Al-Behadili, H.
AU - Grumpe, A.
AU - Wöhler, C.
PY - 2016
SP - 287
EP - 294
DO - 10.5220/0005674202870294

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