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Visual-Interactive Similarity Search for Complex Objects by Example of Soccer Player Analysis

Topics: High-Dimensional Data and Dimensionality Reduction; Information and Scientific Visualization; Interface and Interaction Techniques for Visualization; Visual Data Analysis and Knowledge Discovery; Visual Representation and Interaction; Visualization Applications

Authors: Jürgen Bernard 1 ; Christian Ritter 1 ; David Sessler 1 ; Matthias Zeppelzauer 2 ; Jörn Kohlhammer 3 and Dieter Fellner 3

Affiliations: 1 Technische Universität Darmstadt, Germany ; 2 St. Pölten University of Applied Sciences, Austria ; 3 Technische Universität Darmstadt and Fraunhofer Institute for Computer Graphics Research, Germany

ISBN: 978-989-758-228-8

Keyword(s): Information Visualization, Visual Analytics, Active Learning, Similarity Search, Similarity Learning, Distance Measures, Feature Selection, Complex Data Objects, Soccer Player Analysis, Information Retrieval.

Related Ontology Subjects/Areas/Topics: Abstract Data Visualization ; Computer Vision, Visualization and Computer Graphics ; General Data Visualization ; High-Dimensional Data and Dimensionality Reduction ; Information and Scientific Visualization ; Interface and Interaction Techniques for Visualization ; Visual Data Analysis and Knowledge Discovery ; Visual Representation and Interaction ; Visualization Applications

Abstract: The definition of similarity is a key prerequisite when analyzing complex data types in data mining, information retrieval, or machine learning. However, the meaningful definition is often hampered by the complexity of data objects and particularly by different notions of subjective similarity latent in targeted user groups. Taking the example of soccer players, we present a visual-interactive system that learns users’ mental models of similarity. In a visual-interactive interface, users are able to label pairs of soccer players with respect to their subjective notion of similarity. Our proposed similarity model automatically learns the respective concept of similarity using an active learning strategy. A visual-interactive retrieval technique is provided to validate the model and to execute downstream retrieval tasks for soccer player analysis. The applicability of the approach is demonstrated in different evaluation strategies, including usage scenarions and cross-validation tests.

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Paper citation in several formats:
Bernard J., Ritter C., Sessler D., Zeppelzauer M., Kohlhammer J. and Fellner D. (2017). Visual-Interactive Similarity Search for Complex Objects by Example of Soccer Player Analysis.In Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: IVAPP, (VISIGRAPP 2017) ISBN 978-989-758-228-8, pages 75-87. DOI: 10.5220/0006116400750087

@conference{ivapp17,
author={Jürgen Bernard and Christian Ritter and David Sessler and Matthias Zeppelzauer and Jörn Kohlhammer and Dieter Fellner},
title={Visual-Interactive Similarity Search for Complex Objects by Example of Soccer Player Analysis},
booktitle={Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: IVAPP, (VISIGRAPP 2017)},
year={2017},
pages={75-87},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006116400750087},
isbn={978-989-758-228-8},
}

TY - CONF

JO - Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: IVAPP, (VISIGRAPP 2017)
TI - Visual-Interactive Similarity Search for Complex Objects by Example of Soccer Player Analysis
SN - 978-989-758-228-8
AU - Bernard J.
AU - Ritter C.
AU - Sessler D.
AU - Zeppelzauer M.
AU - Kohlhammer J.
AU - Fellner D.
PY - 2017
SP - 75
EP - 87
DO - 10.5220/0006116400750087

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