INTRODUCTION Global illumination is the physically accurate calculation of lighting in an environment. It is computationally expensive for static environments and even more so for dynamic environments. Not only are many images required for an animation, but the calculation involved increases with the presence of moving objects. In static environments, global illumination algorithms can precompute a lighting solution and reuse it whenever the viewpoint changes, but in dynamic environments, any moving object or light potentially affects the illumination of every other object in a scene. To guarantee accuracy, the algorithm has to recompute the entire lighting solution for each frame. This paper describes a perceptually-based technique that can dramatically reduce this computational load. The technique may also be used in image based rendering, geometry level of detail selection, realistic image synthesis, video telephony and video compression. Perceptually-based rendering operat

Lossy compression algorithms used in digital video systems produce artifacts whose visibility strongly depends on the actual image content. Simple error measures such as RMSE or PSNR, albeit popular, ignore this important fact and are only a mediocre predictor of perceived quality. Many applications require more reliable assessment methods. This paper discusses issues in vision modeling for perceptual video quality assessment (PVQA). Its purpose is not to describe a particular model or system, but rather to summarize and to provide pointers to up-to-date knowledge of important characteristics of the human visual system, to explain how these characteristics may be incorporated in vision models for PVQA, to give a brief overview of the state-of-the-art and current efforts in this field, and to outline directions for future research.

The perceived quality of computer graphics imagery depends on the accuracy of the rendered frames, as well as the capabilities of the human visual system. Fully detailed, high fidelity frames still take many minutes even hours to render on today's computers. The human eye is physically incapable of capturing a moving scene in full detail. We sense image detail only in a 2 # foveal region, relying on rapid eye movements, or saccades, to jump between points of interest. Our brain then reassembles these glimpses into a coherent, but inevitably imperfect, visual percept of the environment. In the process, we literally lose sight of the unimportant details. In this paper, we demonstrate how properties of the human visual system, in particular inattentional blindness, can be exploited to accelerate the rendering of animated sequences by applying a priori knowledge of a viewer's task focus. We show in a controlled experimental setting how human subjects will consistently fail to notice degradations in the quality of image details unrelated to their assigned task, even when these details fall under the viewers' gaze. We then build on these observations to create a perceptual rendering framework that combines predetermined task maps with spatiotemporal contrast sensitivity to guide a progressive animation system which takes full advantage of image-based rendering techniques. We demonstrate this framework with a Radiance ray-tracing implementation that completes its work in a fraction of the normally required time, with few noticeable artifacts for viewers performing the task.

We present a full-reference and a no-reference perceptual video quality metric that incorporate both low-level and high-level aspects of vision. Low-level aspects include color perception, contrast sensitivity, masking as well as artifact analysis. High-level aspects take into account the cognitive behavior of an observer when watching a video by means of semantic segmentation. Using the special case of semantic face segmentation, we evaluate the proposed segmentationdriven perceptual quality metrics using a range of test sequences and demonstrate an improvement of their prediction performance. 1.

High-refresh-rate displays (e. g., 120 Hz) have recently become available on the consumer market and quickly gain on popularity. One of their aims is to reduce the perceived blur created by moving objects that are tracked by the human eye. However, an improvement is only achieved if the video stream is produced at the same high refresh rate (i. e. 120 Hz). Some devices, such as LCD TVs, solve this problem by converting low-refresh-rate content (i. e. 50 Hz PAL) into a higher temporal resolution (i. e. 200 Hz) based on two-dimensional optical flow. In our approach, we will show how rendered three-dimensional images produced by recent graphics hardware can be up-sampled more efficiently resulting in higher quality at the same time. Our algorithm relies on several perceptual findings and preserves the naturalness of the original sequence. A psychophysical study validates our approach and illustrates that temporally up-sampled video streams are preferred over the standard low-rate input by the majority of users. We show that our solution improves task performance on high-refresh-rate displays.

AbstractÐIn this paper, we consider accelerated rendering of high quality walkthrough animation sequences along predefined paths. To improve rendering performance, we use a combination of a hybrid ray tracing and Image-Based Rendering (IBR) technique and a novel perception-based antialiasing technique. In our rendering solution, we derive as many pixels as possible using inexpensive IBR techniques without affecting the animation quality. A perception-based spatiotemporal Animation Quality Metric (AQM) is used to automatically guide such a hybrid rendering. The Image Flow (IF) obtained as a byproduct of the IBR computation is an integral part of the AQM. The final animation quality is enhanced by an efficient spatiotemporal antialiasing which utilizes the IF to perform a motioncompensated filtering. The filter parameters have been tuned using the AQM predictions of animation quality as perceived by the human observer. These parameters adapt locally to the visual pattern velocity. Index TermsÐWalkthrough animation, human perception, video quality metrics, motion-compensated filtering. æ 1

The complexity of most virtual environments prevents them being rendered in real time even on modern graphics hardware. Knowledge of the visual system of the user viewing the environment may be used to significantly reduce image computation times. In this paper, we demonstrate the principle of Change Blindness, a major side effect of brief visual disruptions, including an eye saccade, a flicker, or a blink, where portions of the scene that have changed simultaneously with the visual disruption go unnoticed to the viewer. The onset of the visual disruption inhibits visual attention by swamping the user’s local motion signals, short-circuiting the automatic system that normally draws attention to the change location. Without automatic control, attention is controlled entirely by slower, higher-level mechanisms in the visual system, that search the scene, object by object, until attention finally focuses on the object that is changing. Previous work in perception-based rendering has exploited human visual acuity, to control detail (and therefore time) spent on rendering parts of a scene. In our experiment we show that if changes in rendering detail occur when there is a visual disruption, then visual attention to the change is dramatically slowed as in natural scenes. Therefore, if the principal is used in dynamic animations the change will have passed through the visual field without notice before the viewers ’ attention has picked up the change. Our results clearly show that flaws in the human visual system, such as Change Blindness, can be exploited to reduce rendering times substantially without compromising perceived visual quality.

This paper introduces the foundations of physically accurate rendering in computer graphics. As graphics hardware and processing power improves, we begin to create images in real time that rival real world photography. This paper lays the groundwork for creating such images, working from the most critical component of realistic image generation, the rendering equation. This paper reviews all stages of realistic rendering and physically accurate image generation: description of reflectance properties of materials; solving the rendering equation using Monte Carlo integration; tone reproduction operators to realistically show the images on limited dynamic range displays; and perceptual techniques that can be used to accelerate rendering. 1.

The possibility of perceptual compression using live eye-tracking has been anticipated for some time by many researchers. Among the challenges of real-time eye-gaze based perceptual video compression is how to handle the fast nature of eye movements with a relative complexity of video transcoding and also take into the account a delay associated with transmission in the network. Such delay requires an additional consideration in perceptual encoding because it increases the size of the area that requires high quality coding. In this paper we present a hybrid scheme, one of the first to our knowledge, which combines eye-tracking with fast in-line scene analysis to drastically narrow down the high acuity area without the loss of eye-gaze containment. Keywords: eye-gaze, perceptual encoding, MPEG-2. 1.

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