Perception-driven Accelerated Rendering

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.
Description

        
@article{
10.1111:cgf.13150
, journal = {Computer Graphics Forum}, title = {{
Perception-driven Accelerated Rendering
}}, author = {
Weier, Martin
 and
Stengel, Michael
 and
Myszkowski, Karol
 and
Slusallek, Philipp
 and
Roth, Thorsten
 and
Didyk, Piotr
 and
Eisemann, Elmar
 and
Eisemann, Martin
 and
Grogorick, Steve
 and
Hinkenjann, André
 and
Kruijff, Ernst
 and
Magnor, Marcus
}, year = {
2017
}, publisher = {
The Eurographics Association and John Wiley & Sons Ltd.
}, ISSN = {
1467-8659
}, DOI = {
10.1111/cgf.13150
} }
Citation