Demonstration venue · read-only. Every page can be browsed; the buttons that would change it are switched off. Create an account to run TaxoReview on your own data. A simulation from public publication records: the people listed were not invited and did not agree to review.
? Tutorial for this page

Youngmo Jeong

dblp:158/0721 · DBLP profile ↗
← Back
2ranked-venue papers
0as first author
0since 2021 · last 2019
0000-0002-3441-0978ORCID · corroborated

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

Graphics, computer vision, multimedia, augmented reality and games · 2

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
2 papers
Virtual and augmented reality · 54% Computational fabrication · 23% Computational photography and imaging · 18%

Topics — the 7 heaviest of 7, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Virtual and augmented reality
augmented reality display
0.412019
Foveated AR: dynamically-foveated augmented reality display · ACM Trans. Graph. 2019
Virtual and augmented reality › near-eye display
foveated display
0.412019
Foveated AR: dynamically-foveated augmented reality display · ACM Trans. Graph. 2019
Computational photography and imaging › image display › computational display
gaze-contingent display
0.412019
Foveated AR: dynamically-foveated augmented reality display · ACM Trans. Graph. 2019
Virtual and augmented reality
near-eye display
0.412019
Manufacturing Application-Driven Foveated Near-Eye Displays · IEEE Trans. Vis. Comput. Graph. 2019
Computational fabrication
optical fabrication
0.412019
Manufacturing Application-Driven Foveated Near-Eye Displays · IEEE Trans. Vis. Comput. Graph. 2019
Computational fabrication
computational design
0.112019
Manufacturing Application-Driven Foveated Near-Eye Displays · IEEE Trans. Vis. Comput. Graph. 2019
Geometric modeling and processing › computer-aided design › computer-aided geometric design
freeform surface design
0.112019
Manufacturing Application-Driven Foveated Near-Eye Displays · IEEE Trans. Vis. Comput. Graph. 2019

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

ray tracing · 0.4maxwellian-view display · 0.4machine learning · 0.4holographic optical element · 0.4gaze tracking · 0.43d printing · 0.4
YearPublicationVenuePosition
2019 Foveated AR: dynamically-foveated augmented reality display
abstract
We present a near-eye augmented reality display with resolution and focal depth dynamically driven by gaze tracking. The display combines a traveling microdisplay relayed off a concave half-mirror magnifier for the high-resolution foveal region, with a wide field-of-view peripheral display using a projector-based Maxwellian-view display whose nodal point is translated to follow the viewer's pupil during eye movements using a traveling holographic optical element. The same optics relay an image of the eye to an infrared camera used for gaze tracking, which in turn drives the foveal display location and peripheral nodal point. Our display supports accommodation cues by varying the focal depth of the microdisplay in the foveal region, and by rendering simulated defocus on the "always in focus" scanning laser projector used for peripheral display. The resulting family of displays significantly improves on the field-of-view, resolution, and form-factor tradeoff present in previous augmented reality designs. We show prototypes supporting 30, 40 and 60 cpd foveal resolution at a net 85° × 78° field of view per eye.
Jonghyun Kim 0006, Youngmo Jeong, Michael Stengel, Kaan Aksit, Rachel A. Albert, Ben Boudaoud, Trey Greer, Joohwan Kim, Ward Lopes, Alexander Majercik, Peter Shirley, Josef B. Spjut, Morgan McGuire, David P. Luebke
ACM Trans. Graph.2
2019 Manufacturing Application-Driven Foveated Near-Eye Displays
abstract
Traditional optical manufacturing poses a great challenge to near-eye display designers due to large lead times in the order of multiple weeks, limiting the abilities of optical designers to iterate fast and explore beyond conventional designs. We present a complete near-eye display manufacturing pipeline with a day lead time using commodity hardware. Our novel manufacturing pipeline consists of several innovations including a rapid production technique to improve surface of a 3D printed component to optical quality suitable for near-eye display application, a computational design methodology using machine learning and ray tracing to create freeform static projection screen surfaces for near-eye displays that can represent arbitrary focal surfaces, and a custom projection lens design that distributes pixels non-uniformly for a foveated near-eye display hardware design candidate. We have demonstrated untethered augmented reality near-eye display prototypes to assess success of our technique, and show that a ski-goggles form factor, a large monocular field of view$(30^{o}\times 55^{o})$, and a resolution of 12 cycles per degree can be achieved.
Kaan Aksit, Praneeth Chakravarthula, Kishore Rathinavel, Youngmo Jeong, Rachel A. Albert, Henry Fuchs, David P. Luebke
IEEE Trans. Vis. Comput. Graph.4