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Authors: Hakan Cevikalp ; Jakob Verbeek ; Frédéric Jurie and Alexander Kläser

Affiliation: Inria Rhone-Alpes, France

ISBN: 978-989-8111-21-0

ISSN: 2184-4321

Keyword(s): Constrained clustering, dimensionality reduction, image segmentation, metric learning, pairwise constraints, semi-supervised learning, spectral clustering.

Related Ontology Subjects/Areas/Topics: Computer Vision, Visualization and Computer Graphics ; Feature Extraction ; Features Extraction ; Image and Video Analysis ; Informatics in Control, Automation and Robotics ; Segmentation and Grouping ; Signal Processing, Sensors, Systems Modeling and Control

Abstract: To deal with the problem of insufficient labeled data, usually side information – given in the form of pairwise equivalence constraints between points – is used to discover groups within data. However, existing methods using side information typically fail in cases with high-dimensional spaces. In this paper, we address the problem of learning from side information for high-dimensional data. To this end, we propose a semi-supervised dimensionality reduction scheme that incorporates pairwise equivalence constraints for finding a better embedding space, which improves the performance of subsequent clustering and classification phases. Our method builds on the assumption that points in a sufficiently small neighborhood tend to have the same label. Equivalence constraints are employed to modify the neighborhoods and to increase the separability of different classes. Experimental results on high-dimensional image data sets show that integrating side information into the dimensionality red uction improves the clustering and classification performance. (More)

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Paper citation in several formats:
Cevikalp, H.; Verbeek, J.; Jurie, F. and Kläser, A. (2008). SEMI-SUPERVISED DIMENSIONALITY REDUCTION USING PAIRWISE EQUIVALENCE CONSTRAINTS.In Proceedings of the Third International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2008) ISBN 978-989-8111-21-0, pages 489-496. DOI: 10.5220/0001070304890496

@conference{visapp08,
author={Hakan Cevikalp and Jakob Verbeek and Frédéric Jurie and Alexander Kläser},
title={SEMI-SUPERVISED DIMENSIONALITY REDUCTION USING PAIRWISE EQUIVALENCE CONSTRAINTS},
booktitle={Proceedings of the Third International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2008)},
year={2008},
pages={489-496},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001070304890496},
isbn={978-989-8111-21-0},
}

TY - CONF

JO - Proceedings of the Third International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2008)
TI - SEMI-SUPERVISED DIMENSIONALITY REDUCTION USING PAIRWISE EQUIVALENCE CONSTRAINTS
SN - 978-989-8111-21-0
AU - Cevikalp, H.
AU - Verbeek, J.
AU - Jurie, F.
AU - Kläser, A.
PY - 2008
SP - 489
EP - 496
DO - 10.5220/0001070304890496

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