Perceptual models for high-refresh-rate rendering

Rendering realistic images requires substantial computational power. With new high-refresh-rate displays as well as the renaissance of virtual reality (VR) and augmented reality (AR), one cannot expect that GPU performance will scale fast enough to meet the requirements of immersive photo-realistic rendering with current rendering techniques. In this dissertation, I follow the dual of the well-known computer vision approach: vision is inverse graphics: to improve graphical algorithms, I consider the operation of the human visual system. I propose to model and exploit the limitations of the visual system in the context of novel high-refresh-rate displays; specifically, I focus on spatio-temporal perception, a topic that has received remarkably less attention than spatial-only perception so far. I present three main contributions. First, I demonstrate the validity of the perceptual approach by presenting a conceptually simple rendering technique motivated by our eyes' limited sensitivity to high spatio-temporal change which reduces the rendering load and transmission requirement of current-generation VR headsets without introducing perceivable visual artefacts. Second, I present two visual models related to motion perception: (a) a metric for detecting flicker; and (b) a comprehensive visual model to predict perceived motion quality on monitors with arbitrary refresh rates and monitor resolutions. Third, I propose an adaptive rendering algorithm that utilises the proposed models. All algorithms operate on physical colorimetric units (instead of display-referenced pixel values), for which I provide the appropriate display measurements and models. All proposed algorithms and visual models are calibrated and validated with psychophysical experiments

Modelling Surround-aware Contrast Sensitivity for HDR Displays

Despite advances in display technology, many existing applications rely on psychophysical datasets of human perception gathered using older, sometimes outdated displays. As a result, there exists the underlying assumption that such measurements can be carried over to the new viewing conditions of more modern technology. We have conducted a series of psychophysical experiments to explore contrast sensitivity using a state-of-the-art HDR display, taking into account not only the spatial frequency and luminance of the stimuli but also their surrounding luminance levels. From our data, we have derived a novel surroundaware contrast sensitivity function (CSF), which predicts human contrast sensitivity more accurately. We additionally provide a practical version that retains the benefits of our full model, while enabling easy backward compatibility and consistently producing good results across many existing applications that make use of CSF models. We show examples of effective HDR video compression using a transfer function derived from our CSF, tone-mapping, and improved accuracy in visual difference prediction

Perceptual modelling for 2D and 3D

Livrable D1.1 du projet ANR PERSEECe rapport a été réalisé dans le cadre du projet ANR PERSEE (n° ANR-09-BLAN-0170). Exactement il correspond au livrable D1.1 du projet

Perceptual Visibility Model for Temporal Contrast Changes in Periphery

Modeling perception is critical for many applications and developments in computer graphics to optimize and evaluate content generation techniques. Most of the work to date has focused on central (foveal) vision. However, this is insufficient for novel wide-field-of-view display devices, such as virtual and augmented reality headsets. Furthermore, the perceptual models proposed for the fovea do not readily extend to the off-center, peripheral visual field, where human perception is drastically different. In this paper, we focus on modeling the temporal aspect of visual perception in the periphery. We present new psychophysical experiments that measure the sensitivity of human observers to different spatio-temporal stimuli across a wide field of view. We use the collected data to build a perceptual model for the visibility of temporal changes at different eccentricities in complex video content. Finally, we discuss, demonstrate, and evaluate several problems that can be addressed using our technique. First, we show how our model enables injecting new content into the periphery without distracting the viewer, and we discuss the link between the model and human attention. Second, we demonstrate how foveated rendering methods can be evaluated and optimized to limit the visibility of temporal aliasing

Aerospace medicine and biology: A continuing bibliography with indexes, supplement 128, May 1974

This special bibliography lists 282 reports, articles, and other documents introduced into the NASA scientific and technical information system in April 1974

Perceptual modelling for 2D and 3D

Livrable D1.1 du projet ANR PERSEECe rapport a été réalisé dans le cadre du projet ANR PERSEE (n° ANR-09-BLAN-0170). Exactement il correspond au livrable D1.1 du projet

Aerospace medicine and biology: A continuing bibliography with indexes, supplement 203

This bibliography lists 150 reports, articles, and other documents introduced into the NASA scientific and technical information system in January 1980

Just noticeable distortion model and its application in image processing

Master'sMASTER OF ENGINEERIN

Overview of research in progress at the Center of Excellence

The Center of Excellence (COE) was created nine years ago to facilitate active collaboration between the scientists at Ames Research Center and the Stanford Psychology Department. Significant interchange of ideas and personnel continues between Stanford and participating groups at NASA-Ames; the COE serves its function well. This progress report is organized into sections divided by project. Each section contains a list of investigators, a background statement, progress report, and a proposal for work during the coming year. The projects are: Algorithms for development and calibration of visual systems, Visually optimized image compression, Evaluation of advanced piloting displays, Spectral representations of color, Perception of motion in man and machine, Automation and decision making, and Motion information used for navigation and control