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Wuyao Shen

dblp:09/8378 · DBLP profile ↗
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1ranked-venue papers
1as first author
0since 2021 · last 2016
—ORCID · unresolved

Domains — the database's venue-derived domains; a paper can count in several

Graphics, computer vision, multimedia, augmented reality and games · 1 · 1 first-author

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer graphics and multimedia
1 paper
Visual content generation and editing · 44% Visualization and visual analytics · 44% Virtual and augmented reality · 13%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Visualization and visual analytics › perception
color vision deficiency
0.212016
Seamless visual sharing with color vision deficiencies · ACM Trans. Graph. 2016
Visual content generation and editing
image recoloring
0.212016
Seamless visual sharing with color vision deficiencies · ACM Trans. Graph. 2016
Virtual and augmented reality › 3d display
stereoscopic display
0.112016
Seamless visual sharing with color vision deficiencies · ACM Trans. Graph. 2016

Methods — techniques the papers use, named apart from their topics

user study · 0.2objective function optimization · 0.2
YearPublicationVenuePosition
2016 Seamless visual sharing with color vision deficiencies
abstract
Approximately 250 million people suffer from color vision deficiency (CVD). They can hardly share the same visual content with normal-vision audiences. In this paper, we propose the first system that allows CVD and normal-vision audiences to share the same visual content simultaneously. The key that we can achieve this is because the ordinary stereoscopic display (non-autostereoscopic ones) offers users two visual experiences (with and without wearing stereoscopic glasses). By allocating one experience to CVD audiences and one to normal-vision audiences, we allow them to share. The core problem is to synthesize an image pair, that when they are presented binocularly, CVD audiences can distinguish the originally indistinguishable colors; and when it is in monocular presentation, normal-vision audiences cannot distinguish its difference from the original image. We solve the image-pair recoloring problem by optimizing an objective function that minimizes the color deviation for normal-vision audiences, and maximizes the color distinguishability and binocular fusibility for CVD audiences. Our method is extensively evaluated via multiple quantitative experiments and user studies. Convincing results are obtained in all our test cases.
Wuyao Shen, Xinghong Hu, Tien-Tsin Wong
ACM Trans. Graph.1