A Taxonomy and Evaluation of Dense Light Field Depth Estimation Algorithms

Ole Johannsen; Katrin Honauer; Bastian Goldluecke; Anna Alperovich; Federica Battisti; Yunsu Bok; Michele Brizzi; Marco Carli; Gyeongmin Choe; Maximilian Diebold; Marcel Gutsche; Hae Gon Jeon; In So Kweon; Jaesik Park; Jinsun Park; Hendrik Schilling; Hao Sheng; Lipeng Si; Michael Strecke; Antonin Sulc; Yu Wing Tai; Qing Wang; Ting Chun Wang; Sven Wanner; Zhang Xiong; Jingyi Yu; Shuo Zhang; Hao Zhu

doi:10.1109/CVPRW.2017.226

A Taxonomy and Evaluation of Dense Light Field Depth Estimation Algorithms

Ole Johannsen, Katrin Honauer, Bastian Goldluecke, Anna Alperovich, Federica Battisti, Yunsu Bok, Michele Brizzi, Marco Carli, Gyeongmin Choe, Maximilian Diebold, Marcel Gutsche, Hae Gon Jeon, In So Kweon, Jaesik Park, Jinsun Park, Hendrik Schilling, Hao Sheng, Lipeng Si, Michael Strecke, Antonin SulcYu Wing Tai, Qing Wang, Ting Chun Wang, Sven Wanner, Zhang Xiong, Jingyi Yu, Shuo Zhang, Hao Zhu

School of Computer Science

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

98 Scopus citations

Abstract

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-ofthe- 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.

Original language	English
Title of host publication	Proceedings - 30th IEEE Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2017
Publisher	IEEE Computer Society
Pages	1795-1812
Number of pages	18
ISBN (Electronic)	9781538607336
DOIs	https://doi.org/10.1109/CVPRW.2017.226
State	Published - 22 Aug 2017
Event	30th IEEE Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2017 - Honolulu, United States Duration: 21 Jul 2017 → 26 Jul 2017

Publication series

Name	IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops
Volume	2017-July
ISSN (Print)	2160-7508
ISSN (Electronic)	2160-7516

Conference

Conference	30th IEEE Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2017
Country/Territory	United States
City	Honolulu
Period	21/07/17 → 26/07/17

Access to Document

10.1109/CVPRW.2017.226

Cite this

Johannsen, O., Honauer, K., Goldluecke, B., Alperovich, A., Battisti, F., Bok, Y., Brizzi, M., Carli, M., Choe, G., Diebold, M., Gutsche, M., Jeon, H. G., Kweon, I. S., Park, J., Park, J., Schilling, H., Sheng, H., Si, L., Strecke, M., ... Zhu, H. (2017). A Taxonomy and Evaluation of Dense Light Field Depth Estimation Algorithms. In Proceedings - 30th IEEE Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2017 (pp. 1795-1812). Article 8014960 (IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops; Vol. 2017-July). IEEE Computer Society. https://doi.org/10.1109/CVPRW.2017.226

Johannsen, Ole ; Honauer, Katrin ; Goldluecke, Bastian et al. / A Taxonomy and Evaluation of Dense Light Field Depth Estimation Algorithms. Proceedings - 30th IEEE Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2017. IEEE Computer Society, 2017. pp. 1795-1812 (IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops).

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title = "A Taxonomy and Evaluation of Dense Light Field Depth Estimation Algorithms",

abstract = "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-ofthe- 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.",

author = "Ole Johannsen and Katrin Honauer and Bastian Goldluecke and Anna Alperovich and Federica Battisti and Yunsu Bok and Michele Brizzi and Marco Carli and Gyeongmin Choe and Maximilian Diebold and Marcel Gutsche and Jeon, {Hae Gon} and Kweon, {In So} and Jaesik Park and Jinsun Park and Hendrik Schilling and Hao Sheng and Lipeng Si and Michael Strecke and Antonin Sulc and Tai, {Yu Wing} and Qing Wang and Wang, {Ting Chun} and Sven Wanner and Zhang Xiong and Jingyi Yu and Shuo Zhang and Hao Zhu",

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Johannsen, O, Honauer, K, Goldluecke, B, Alperovich, A, Battisti, F, Bok, Y, Brizzi, M, Carli, M, Choe, G, Diebold, M, Gutsche, M, Jeon, HG, Kweon, IS, Park, J, Park, J, Schilling, H, Sheng, H, Si, L, Strecke, M, Sulc, A, Tai, YW, Wang, Q, Wang, TC, Wanner, S, Xiong, Z, Yu, J, Zhang, S & Zhu, H 2017, A Taxonomy and Evaluation of Dense Light Field Depth Estimation Algorithms. in Proceedings - 30th IEEE Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2017., 8014960, IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, vol. 2017-July, IEEE Computer Society, pp. 1795-1812, 30th IEEE Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2017, Honolulu, United States, 21/07/17. https://doi.org/10.1109/CVPRW.2017.226

A Taxonomy and Evaluation of Dense Light Field Depth Estimation Algorithms. / Johannsen, Ole; Honauer, Katrin; Goldluecke, Bastian et al.
Proceedings - 30th IEEE Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2017. IEEE Computer Society, 2017. p. 1795-1812 8014960 (IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops; Vol. 2017-July).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Johannsen, Ole

AU - Honauer, Katrin

AU - Goldluecke, Bastian

AU - Alperovich, Anna

AU - Battisti, Federica

AU - Bok, Yunsu

AU - Brizzi, Michele

AU - Carli, Marco

AU - Choe, Gyeongmin

AU - Diebold, Maximilian

AU - Gutsche, Marcel

AU - Jeon, Hae Gon

AU - Kweon, In So

AU - Park, Jaesik

AU - Park, Jinsun

AU - Schilling, Hendrik

AU - Sheng, Hao

AU - Si, Lipeng

AU - Strecke, Michael

AU - Sulc, Antonin

AU - Tai, Yu Wing

AU - Wang, Qing

AU - Wang, Ting Chun

AU - Wanner, Sven

AU - Xiong, Zhang

AU - Yu, Jingyi

AU - Zhang, Shuo

AU - Zhu, Hao

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AB - 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-ofthe- 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.

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Johannsen O, Honauer K, Goldluecke B, Alperovich A, Battisti F, Bok Y et al. A Taxonomy and Evaluation of Dense Light Field Depth Estimation Algorithms. In Proceedings - 30th IEEE Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2017. IEEE Computer Society. 2017. p. 1795-1812. 8014960. (IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops). doi: 10.1109/CVPRW.2017.226

A Taxonomy and Evaluation of Dense Light Field Depth Estimation Algorithms

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