CONTINUOUS LEARNING OF SIMPLE VISUAL CONCEPTS USING INCREMENTAL KERNEL DENSITY ESTIMATION

Danijel Skočaj, Matej Kristan, Aleš Leonardis

2008

Abstract

In this paper we propose a method for continuous learning of simple visual concepts. The method continuously associates words describing observed scenes with automatically extracted visual features. Since in our setting every sample is labelled with multiple concept labels, and there are no negative examples, reconstructive representations of the incoming data are used. The associated features are modelled with kernel density probability distribution estimates, which are built incrementally. The proposed approach is applied to the learning of object properties and spatial relations.

Paper Citation

in Harvard Style

Skočaj D., Kristan M. and Leonardis A. (2008). CONTINUOUS LEARNING OF SIMPLE VISUAL CONCEPTS USING INCREMENTAL KERNEL DENSITY ESTIMATION . In Proceedings of the Third International Conference on Computer Vision Theory and Applications - Volume 1: OPRMLT, (VISIGRAPP 2008) ISBN 978-989-8111-21-0, pages 598-604. DOI: 10.5220/0001090405980604

in Bibtex Style

@conference{oprmlt08,
author={Danijel Skočaj and Matej Kristan and Aleš Leonardis},
title={CONTINUOUS LEARNING OF SIMPLE VISUAL CONCEPTS USING INCREMENTAL KERNEL DENSITY ESTIMATION},
booktitle={Proceedings of the Third International Conference on Computer Vision Theory and Applications - Volume 1: OPRMLT, (VISIGRAPP 2008)},
year={2008},
pages={598-604},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001090405980604},
isbn={978-989-8111-21-0},
}

in EndNote Style

TY - CONF
JO - Proceedings of the Third International Conference on Computer Vision Theory and Applications - Volume 1: OPRMLT, (VISIGRAPP 2008)
TI - CONTINUOUS LEARNING OF SIMPLE VISUAL CONCEPTS USING INCREMENTAL KERNEL DENSITY ESTIMATION
SN - 978-989-8111-21-0
AU - Skočaj D.
AU - Kristan M.
AU - Leonardis A.
PY - 2008
SP - 598
EP - 604
DO - 10.5220/0001090405980604