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Journal ArticleDOI

Perception-driven Accelerated Rendering

TLDR
This report presents the key research and models that exploit the limitations of perception to tackle visual quality and workload alike, and presents the open problems and promising future research targeting the question of how to minimize the effort to compute and display only the necessary pixels while still offering a user full visual experience.
Abstract
Advances in computer graphics enable us to create digital images of astonishing complexity and realism. However, processing resources are still a limiting factor. Hence, many costly but desirable aspects of realism are often not accounted for, including global illumination, accurate depth of field and motion blur, spectral effects, etc. especially in real-time rendering. At the same time, there is a strong trend towards more pixels per display due to larger displays, higher pixel densities or larger fields of view. Further observable trends in current display technology include more bits per pixel high dynamic range, wider color gamut/fidelity, increasing refresh rates better motion depiction, and an increasing number of displayed views per pixel stereo, multi-view, all the way to holographic or lightfield displays. These developments cause significant unsolved technical challenges due to aspects such as limited compute power and bandwidth. Fortunately, the human visual system has certain limitations, which mean that providing the highest possible visual quality is not always necessary. In this report, we present the key research and models that exploit the limitations of perception to tackle visual quality and workload alike. Moreover, we present the open problems and promising future research targeting the question of how we can minimize the effort to compute and display only the necessary pixels while still offering a user full visual experience.

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Citations
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Book

Color Appearance Models

TL;DR: This book is a good overview of the most important and relevant literature regarding color appearance models and offers insight into the preferred solutions.

Information processing

TL;DR: A laboratory study is used to examine the effectiveness of various front-sided health claims when used in combination with a full health claim on the back panel to determine how labeling information needs to be presented to effectively allow consumers to understand and use claim information.
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

DeepFovea: neural reconstruction for foveated rendering and video compression using learned statistics of natural videos

TL;DR: This work explores a novel foveated reconstruction method that employs the recent advances in generative adversarial neural networks to reconstruct a plausible peripheral video from a small fraction of pixels provided every frame.
Journal ArticleDOI

Luminance-contrast-aware foveated rendering

TL;DR: A new luminance-contrast-aware foveated rendering technique is proposed which demonstrates that the computational savings of foveate rendering can be significantly improved if local luminance contrast of the image is analyzed and a low-cost predictor is derived.
References
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Journal ArticleDOI

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Journal ArticleDOI

Robust Real-Time Face Detection

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Journal ArticleDOI

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Proceedings ArticleDOI

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Journal ArticleDOI

A model of saliency-based visual attention for rapid scene analysis

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