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EyeCode SIGNED

Perceptual encoding of high fidelity light fields

Total Cost €

EC-Contrib. €

Partnership

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EyeCode project word cloud

Explore the words cloud of the EyeCode project. It provides you a very rough idea of what is the project "EyeCode" about.

binocular frame reduce colour encoding starts performance cues manipulation sufficiently ve mostly stage tedious imagery sufficient replace derive bandwidth cinema pave observer characterise dynamic displays 3d resolution visual data opens computer na span automated human indistinguishable lfs content photographs model perceptually configurations subjective technologies special tremendous optimize ignores impose imaging world iuml first observing hdr limitations video efficient gamut one lf create difference uniform realistic bottleneck focal scene capture luminance area electronic rate metric storage scenes radically enormous image catalogues display generate grand images final progress graphics light approximately

Project "EyeCode" data sheet

The following table provides information about the project.

Coordinator	THE CHANCELLOR MASTERS AND SCHOLARSOF THE UNIVERSITY OF CAMBRIDGE Organization address address: TRINITY LANE THE OLD SCHOOLS city: CAMBRIDGE postcode: CB2 1TN website: www.cam.ac.uk contact info title: n.a. name: n.a. surname: n.a. function: n.a. email: n.a. telephone: n.a. fax: n.a.
Coordinator Country	United Kingdom [UK]
Total cost	1˙868˙855 €
EC max contribution	1˙868˙855 € (100%)
Programme	1. H2020-EU.1.1. (EXCELLENT SCIENCE - European Research Council (ERC))
Code Call	ERC-2016-COG
Funding Scheme	ERC-COG
Starting year	2017
Duration (year-month-day)	from 2017-07-01 to 2022-06-30

Partnership

Take a look of project's partnership.

#	participants	country	role	EC contrib. [€]
1	THE CHANCELLOR MASTERS AND SCHOLARSOF THE UNIVERSITY OF CAMBRIDGE THE CHANCELLOR MASTERS AND SCHOLARSOF THE UNIVERSITY OF CAMBRIDGE Organization address address: TRINITY LANE THE OLD SCHOOLS city: CAMBRIDGE postcode: CB2 1TN website: www.cam.ac.uk contact info title: n.a. name: n.a. surname: n.a. function: n.a. email: n.a. telephone: n.a. fax: n.a.	UK (CAMBRIDGE)	coordinator	1˙868˙855.00

Map

Project objective

One of the grand challenges of computer graphics has been to generate images indistinguishable from photographs for a naïve observer. As this challenge is mostly completed and computer generated imagery starts to replace photographs (product catalogues, special effects in cinema), the next grand challenge is to produce imagery that is indistinguishable from the real-world.

Tremendous progress in capture, manipulation and display technologies opens the potential to achieve this new challenge (at the research stage) in the next 5-10 years. Electronic displays offer sufficient resolution, frame rate, dynamic range, colour gamut and, in some configurations, can produce binocular and focal depth cues. However, most of the work done in this area ignores or does not sufficiently address one of the key aspects of this problem - the performance and limitations of the human visual system.

The objective of this project is to characterise and model the performance and limitations of the human visual system when observing complex dynamic 3D scenes. The scene will span a high dynamic range (HDR) of luminance and provide binocular and focal depth cues. In technical terms, the project aims to create a visual model and difference metric for high dynamic range light fields (HDR-LFs). The visual metric will replace tedious subjective testing and provide the first automated method that can optimize encoding and processing of HDR-LF data.

Perceptually realistic video will impose enormous storage and processing requirements compared to traditional video. The bandwidth of such rich visual content will be the main bottleneck for new imaging and display technologies. Therefore, the final objective of this project is to use the new visual metric to derive an efficient and approximately perceptually uniform encoding of HDR-LFs. Such encoding will radically reduce storage and bandwidth requirements and will pave the way for future highly realistic image and video content.

Publications

List of publications.
year	authors and title	journal	last update
2020	Gyorgy Denes, RafaÅ‚ K. Mantiuk Predicting visible flicker in temporally changing images published pages: , ISSN: , DOI:	Human Vision and Electronic Imaging	2020-03-05
2019	K. Wolski, D. Giunchi, S. Kinuwaki, P. Didyk, K. Myszkowski, A. Steed, R. K. Mantiuk Selecting texture resolution using a taskâ€specific visibility metric published pages: 685-696, ISSN: 0167-7055, DOI: 10.1111/cgf.13871	Computer Graphics Forum 38/7	2020-03-05
2019	Fangcheng Zhong, George Alex Koulieris, George Drettakis, Martin S. Banks, Mathieu Chambe, FrÃ©do Durand, RafaÅ‚ K. Mantiuk DiCE published pages: 1-13, ISSN: 0730-0301, DOI: 10.1145/3355089.3356552	ACM Transactions on Graphics (TOG) 38/6	2020-03-05
2020	Maria Perez-Ortiz, Aliaksei Mikhailiuk, Emin Zerman, Vedad Hulusic, Giuseppe Valenzise, Rafal K. Mantiuk From Pairwise Comparisons and Rating to a Unified Quality Scale published pages: 1139-1151, ISSN: 1057-7149, DOI: 10.1109/tip.2019.2936103	IEEE Transactions on Image Processing 29	2020-03-05
2018	Krzysztof Wolski, Daniele Giunchi, Nanyang Ye, Piotr Didyk, Karol Myszkowski, RadosÅ‚aw Mantiuk, Hans-Peter Seidel, Anthony Steed, RafaÅ‚ K. Mantiuk Dataset and Metrics for Predicting Local Visible Differences published pages: 1-14, ISSN: 0730-0301, DOI: 10.1145/3196493	ACM Transactions on Graphics 37/5	2020-01-21
2018	Mikhailiuk, A; Perez-Ortiz, M; Mantiuk, Rafal Psychometric scaling of TID2013 dataset published pages: , ISSN: , DOI: 10.17863/CAM.26628	In: Atzori, L, (ed.) Proceedings of the 2018 Tenth International Conference on Quality of Multimedia Experience (QoMEX). IEEE: Cagliari, Italy. (2018) 1	2020-01-21
2018	Emin Zerman, Vedad Hulusic, Giuseppe Valenzise, RafaÅ‚ K. Mantiuk, FrÃ©dÃ©ric Dufaux The Relation Between MOS and Pairwise Comparisons and the Importance of Cross-Content Comparisons published pages: 1-6, ISSN: 2470-1173, DOI: 10.2352/issn.2470-1173.2018.14.hvei-517	Electronic Imaging 2018/14	2020-01-21
2019	Gyorgy Denes, Kuba Maruszczyk, George Ash, Rafal Mantiuk Temporal Resolution Multiplexing: Exploiting the limitations of spatio-temporal vision for more efficient VR rendering published pages: 1-1, ISSN: 1077-2626, DOI: 10.1109/tvcg.2019.2898741	IEEE Transactions on Visualization and Computer Graphics 1	2020-01-21

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The information about "EYECODE" are provided by the European Opendata Portal: CORDIS opendata.