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EyeCode SIGNED

Perceptual encoding of high fidelity light fields

Total Cost €

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EC-Contrib. €

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Partnership

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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 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

year authors and title journal last update
List of publications.
2020 Gyorgy Denes, Rafał 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 task‐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, Frédo Durand, Rafał 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, Radosław Mantiuk, Hans-Peter Seidel, Anthony Steed, Rafał 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, Rafał K. Mantiuk, Frédéric 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.

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