A Taxonomy and Evaluation of Dense Light Field Depth Estimation Algorithms

Johannsen, Ole; Honauer, Katrin; Goldlücke, Bastian; Alperovich, Anna; Battisti, Federica; Bok, Yunsu; Brizzi, Michele; Carli, Marco; Strecke, Michael; Sulc, Antonin

A Taxonomy and Evaluation of Dense Light Field Depth Estimation Algorithms

Dateien

Zu diesem Dokument gibt es keine Dateien.

Datum

2017

Autor:innen

Johannsen, Ole

Honauer, Katrin

Goldlücke, Bastian

Alperovich, Anna

Battisti, Federica

Bok, Yunsu

Brizzi, Michele

Carli, Marco

Strecke, Michael

Sulc, Antonin

et al.

DOI (zitierfähiger Link)

https://doi.org/10.1109/CVPRW.2017.226

Angaben zur Forschungsförderung

European Union (EU): 336978

Projekt

LIA - Light Field Imaging and Analysis

Sammlungen

Informatik und Informationswissenschaft

Publikationstyp

Beitrag zu einem Konferenzband

Publikationsstatus

Published

Erschienen in

CVPRW 2017 : 30th IEEE Conference on Computer Vision and Pattern Recognition Workshops : proceedings : 21-26 July 2016, Honolulu, Hawaii. Piscataway, NJ: IEEE, 2017, pp. 1795-1812. eISSN 2160-7516. ISBN 978-1-5386-0733-6. Available under: doi: 10.1109/CVPRW.2017.226

Zusammenfassung

This paper presents the results of the depth estimation challenge for dense light fields, which took place at the second workshop on Light Fields for Computer Vision (LF4CV) in conjunction with CVPR 2017. The challenge consisted of submission to a recent benchmark [7], which allows a thorough performance analysis. While individual results are readily available on the benchmark web page http://www.lightfield-analysis.net, we take this opportunity to give a detailed overview of the current participants. Based on the algorithms submitted to our challenge, we develop a taxonomy of light field disparity estimation algorithms and give a report on the current state-of-the-art. In addition, we include more comparative metrics, and discuss the relative strengths and weaknesses of the algorithms. Thus, we obtain a snapshot of where light field algorithm development stands at the moment and identify aspects with potential for further improvement.

Fachgebiet (DDC)

004 Informatik

Konferenz

2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), Proceedings, 21. Juli 2017 - 26. Juli 2017, Honolulu, HI, USA

Zitieren

ISO 690

JOHANNSEN, Ole, Katrin HONAUER, Bastian GOLDLÜCKE, Anna ALPEROVICH, Federica BATTISTI, Yunsu BOK, Michele BRIZZI, Marco CARLI, Michael STRECKE, Antonin SULC, 2017. A Taxonomy and Evaluation of Dense Light Field Depth Estimation Algorithms. 2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), Proceedings. Honolulu, HI, USA, 21. Juli 2017 - 26. Juli 2017. In: CVPRW 2017 : 30th IEEE Conference on Computer Vision and Pattern Recognition Workshops : proceedings : 21-26 July 2016, Honolulu, Hawaii. Piscataway, NJ: IEEE, 2017, pp. 1795-1812. eISSN 2160-7516. ISBN 978-1-5386-0733-6. Available under: doi: 10.1109/CVPRW.2017.226

BibTex

@inproceedings{Johannsen2017-07Taxon-41509,
  year={2017},
  doi={10.1109/CVPRW.2017.226},
  title={A Taxonomy and Evaluation of Dense Light Field Depth Estimation Algorithms},
  isbn={978-1-5386-0733-6},
  publisher={IEEE},
  address={Piscataway, NJ},
  booktitle={CVPRW 2017 : 30th IEEE Conference on Computer Vision and Pattern Recognition Workshops : proceedings : 21-26 July 2016, Honolulu, Hawaii},
  pages={1795--1812},
  author={Johannsen, Ole and Honauer, Katrin and Goldlücke, Bastian and Alperovich, Anna and Battisti, Federica and Bok, Yunsu and Brizzi, Michele and Carli, Marco and Strecke, Michael and Sulc, Antonin}
}

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Universitätsbibliographie

Ja