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Michael Stengel

Researcher at Nvidia

Publications -  28
Citations -  836

Michael Stengel is an academic researcher from Nvidia. The author has contributed to research in topics: Rendering (computer graphics) & Eye tracking. The author has an hindex of 12, co-authored 25 publications receiving 579 citations. Previous affiliations of Michael Stengel include Otto-von-Guericke University Magdeburg & Delft University of Technology.

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Journal ArticleDOI

Near-Eye Display and Tracking Technologies for Virtual and Augmented Reality

TL;DR: This state‐of‐the‐art report investigates the background theory of perception and vision as well as the latest advancements in display engineering and tracking technologies involved in near‐eye displays.
Journal ArticleDOI

Foveated AR: dynamically-foveated augmented reality display

TL;DR: This work presents a near-eye augmented reality display with resolution and focal depth dynamically driven by gaze tracking, and shows prototypes supporting 30, 40 and 60 cpd foveal resolution at a net 85° × 78° field of view per eye.
Proceedings ArticleDOI

NVGaze: An Anatomically-Informed Dataset for Low-Latency, Near-Eye Gaze Estimation

TL;DR: This work creates a synthetic dataset using anatomically-informed eye and face models with variations in face shape, gaze direction, pupil and iris, skin tone, and external conditions, and trains neural networks performing with sub-millisecond latency.
Journal ArticleDOI

Adaptive Image-Space Sampling for Gaze-Contingent Real-time Rendering

TL;DR: This work proposes an algorithm that only shades visible features of the image while cost‐effectively interpolating the remaining features without affecting perceived quality, and introduces a sampling scheme that incorporates multiple aspects of the human visual system: acuity, eye motion, contrast, and brightness adaptation.
Journal ArticleDOI

Garment Replacement in Monocular Video Sequences

TL;DR: A semi-automatic approach to exchange the clothes of an actor for arbitrary virtual garments in conventional monocular video footage as a postprocess using a parameterized body model, which serves as an animated mannequin for simulating the virtual garment.