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    Felizberta Lo Padilla Tong School of Social SciencesIp Ying To Lee Yu Yee School of Humanities and LanguagesRita Tong Liu School of Business and Hospitality ManagementS.K. Yee School of Health SciencesYam Pak Charitable Foundation School of Computing and Information Sciences
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  4. Colorblind-shareable videos by synthesizing temporal-coherent polynomial coefficients
 
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Colorblind-shareable videos by synthesizing temporal-coherent polynomial coefficients

Author(s)
Liu, Xueting  
Author(s)
Hu, X.
Zhang, Z.
Xia, M.
Li, C.
Wong, T.-T.
Date Issued
2019
Publisher
Association for Computing Machinery
Journal
ACM Transactions on Graphics
Volume
38
Issue
6
Abstract
To share the same visual content between color vision deficiencies (CVD) and normal-vision people, attempts have been made to allocate the two visual experiences of a binocular display (wearing and not wearing glasses) to CVD and normal-vision audiences. However, existing approaches only work for still images. Although state-of-the-art temporal filtering techniques can be applied to smooth the per-frame generated content, they may fail to maintain the multiple binocular constraints needed in our applications, and even worse, sometimes introduce color inconsistency (same color regions map to different colors). In this paper, we propose to train a neural network to predict the temporal coherent polynomial coefficients in the domain of global color decomposition. This indirect formulation solves the color inconsistency problem. Our key challenge is to design a neural network to predict the temporal coherent coefficients, while maintaining all required binocular constraints. Our method is evaluated on various videos and all metrics confirm that it outperforms all existing solutions.
URI
https://repository.sfu.edu.hk/handle/sfu/827
DOI
10.1145/3355089.3356534
SFU Affiliated Publication
Yes
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