Image Quality Assessment for Photo-consistency Evaluation on Planar Classification in Urban Scenes
Marie-Anne Bauda, Sylvie Chambon, Pierre Gurdjos, Vincent Charvillat
2015
Abstract
In the context of semantic segmentation of urban scenes, the calibrated multi-views and the flatness assumption are commonly used to estimate a warped image based on the homography estimation. In order to classify planar and non-planar areas, we propose an evaluation protocol that compares several Image Quality Assessments (IQA) between a reference zone and its warped zone. We show that cosine angle distance-based measures are more efficient than euclidean distance-based for the planar/non-planar classification and that the Universal Quality Image (UQI) measure outperforms the other evaluated measures.
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Paper Citation
in Harvard Style
Bauda M., Chambon S., Gurdjos P. and Charvillat V. (2015). Image Quality Assessment for Photo-consistency Evaluation on Planar Classification in Urban Scenes . In Proceedings of the International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM, ISBN 978-989-758-076-5, pages 328-333. DOI: 10.5220/0005222603280333
in Bibtex Style
@conference{icpram15,
author={Marie-Anne Bauda and Sylvie Chambon and Pierre Gurdjos and Vincent Charvillat},
title={Image Quality Assessment for Photo-consistency Evaluation on Planar Classification in Urban Scenes},
booktitle={Proceedings of the International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,},
year={2015},
pages={328-333},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005222603280333},
isbn={978-989-758-076-5},
}
in EndNote Style
TY - CONF
JO - Proceedings of the International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,
TI - Image Quality Assessment for Photo-consistency Evaluation on Planar Classification in Urban Scenes
SN - 978-989-758-076-5
AU - Bauda M.
AU - Chambon S.
AU - Gurdjos P.
AU - Charvillat V.
PY - 2015
SP - 328
EP - 333
DO - 10.5220/0005222603280333