MOTION SEGMENTATION THROUGH FACTORIZATION - APPLICATION TO NIGHT DRIVING ASSISTANCE

Carme Julià, Joan Serrat, Antonio López, Felipe Lumbreras, Dani Ponsa, Thorsten Graf

2006

Abstract

Intelligent vehicles are those equipped with sensors and information control systems that can assist human driving. In this context, we address the problem of detecting vehicles at night. The aim is to distinguish vehicles from lamp posts and traffic sign reflections by grouping the blob trajectories according to their apparent motion. We have adapted two factorization techniques, originally designed to estimate the scene structure from motion: the Costeira–Kanade and the Han–Kanade, named after their authors. Results on both vehicle existence in the field of view and motion segmentation are reported.

Paper Citation

in Harvard Style

Julià C., Serrat J., López A., Lumbreras F., Ponsa D. and Graf T. (2006). MOTION SEGMENTATION THROUGH FACTORIZATION - APPLICATION TO NIGHT DRIVING ASSISTANCE . In Proceedings of the First International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, ISBN 972-8865-40-6, pages 270-277. DOI: 10.5220/0001362802700277

in Bibtex Style

@conference{visapp06,
author={Carme Julià and Joan Serrat and Antonio López and Felipe Lumbreras and Dani Ponsa and Thorsten Graf},
title={MOTION SEGMENTATION THROUGH FACTORIZATION - APPLICATION TO NIGHT DRIVING ASSISTANCE},
booktitle={Proceedings of the First International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP,},
year={2006},
pages={270-277},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001362802700277},
isbn={972-8865-40-6},
}

in EndNote Style

TY - CONF
JO - Proceedings of the First International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP,
TI - MOTION SEGMENTATION THROUGH FACTORIZATION - APPLICATION TO NIGHT DRIVING ASSISTANCE
SN - 972-8865-40-6
AU - Julià C.
AU - Serrat J.
AU - López A.
AU - Lumbreras F.
AU - Ponsa D.
AU - Graf T.
PY - 2006
SP - 270
EP - 277
DO - 10.5220/0001362802700277