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Authors: Artur Santos Nascimento ; Welerson Augusto Lino de Jesus Melo ; Beatriz Trinchão Andrade and Daniel Oliveira Dantas

Affiliation: Departamento de Computação, Universidade Federal de Sergipe, São Cristóvão, SE, Brazil

Keyword(s): High Dynamic Range Images, Feature Point Detection, Feature Point Description.

Abstract: Feature point (FP) detection and description are processes that detect and extract characteristics from images. Several computer vision applications rely on the usage of FPs. Most FP descriptors are designed to support low dynamic range (LDR) images as input. However, high dynamic range (HDR) images can show details in bright and shadowed areas that LDR images can not. For that reason, the interest in HDR imagery as input in the detection and description processes has been increasing. Previous studies have explored FP detectors in HDR images. However, none have presented FP descriptors designed for HDR images. This study compares the FP matching performance of description vectors generated from LDR and HDR images. The FPs were detected and described using a version of the SIFT algorithm adapted to support HDR images. The FP matching performance of the algorithm was evaluated with the mAP metric. In all cases, using HDR images increased the mAP values when compared to LDR images.

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Paper citation in several formats:
Nascimento, A.; Melo, W.; Andrade, B. and Dantas, D. (2022). Evaluation of a Local Descriptor for HDR Images. In Proceedings of the 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2022) - Volume 4: VISAPP; ISBN 978-989-758-555-5; ISSN 2184-4321, SciTePress, pages 299-306. DOI: 10.5220/0010779700003124

@conference{visapp22,
author={Artur Santos Nascimento. and Welerson Augusto Lino de Jesus Melo. and Beatriz Trinchão Andrade. and Daniel Oliveira Dantas.},
title={Evaluation of a Local Descriptor for HDR Images},
booktitle={Proceedings of the 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2022) - Volume 4: VISAPP},
year={2022},
pages={299-306},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010779700003124},
isbn={978-989-758-555-5},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2022) - Volume 4: VISAPP
TI - Evaluation of a Local Descriptor for HDR Images
SN - 978-989-758-555-5
IS - 2184-4321
AU - Nascimento, A.
AU - Melo, W.
AU - Andrade, B.
AU - Dantas, D.
PY - 2022
SP - 299
EP - 306
DO - 10.5220/0010779700003124
PB - SciTePress

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