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Authors: Victoria Manousaki ; Konstantinos Papoutsakis and Antonis Argyros

Affiliation: University of Crete and FORTH, Greece

Keyword(s): Action Classification, K Nearest Neighbours, Support Vector Machines, Radial Basis Function Neural Network, Bag of Visual Words, Motion Boundary Histograms.

Abstract: The Bags of Visua lWords (BoVWs) framework has been applied successfully to several computer vision tasks. In this work we are particularly interested on its application to the problem of action recognition/classification. The key design decisions for a method that follows the BoVWs framework are (a) the visual features to be employed, (b) the size of the codebook to be used for representing a certain action and (c) the classifier applied to the developed representation to solve the classification task. We perform several experiments to investigate a variety of options regarding all the aforementioned design parameters. We also propose a new feature type and we suggest a method that determines automatically the size of the codebook. The experimental results show that our proposals produce results that are competitive to the outcomes of state of the art methods.

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Paper citation in several formats:
Manousaki, V.; Papoutsakis, K. and Argyros, A. (2018). Evaluating Method Design Options for Action Classification based on Bags of Visual Words. In Proceedings of the 13th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2018) - Volume 5: VISAPP; ISBN 978-989-758-290-5; ISSN 2184-4321, SciTePress, pages 185-192. DOI: 10.5220/0006544201850192

@conference{visapp18,
author={Victoria Manousaki. and Konstantinos Papoutsakis. and Antonis Argyros.},
title={Evaluating Method Design Options for Action Classification based on Bags of Visual Words},
booktitle={Proceedings of the 13th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2018) - Volume 5: VISAPP},
year={2018},
pages={185-192},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006544201850192},
isbn={978-989-758-290-5},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the 13th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2018) - Volume 5: VISAPP
TI - Evaluating Method Design Options for Action Classification based on Bags of Visual Words
SN - 978-989-758-290-5
IS - 2184-4321
AU - Manousaki, V.
AU - Papoutsakis, K.
AU - Argyros, A.
PY - 2018
SP - 185
EP - 192
DO - 10.5220/0006544201850192
PB - SciTePress

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