Level of Detail (LoD) techniques for real-time... In this paper, we are particularly interested in the problem of realistic collision simulation in scenes where large numbers of objects are colliding and processing must occur in real-time. An interruptible and therefore degradable collision handling mechanism is used and the perceptual impact of this degradation is explored. We look for ways in which we can optimise the realism of such simulations and describe a series of psychophysical experiments that investigated different factors affecting collision perception, including eccentricity, separation, distractors, causality and accuracy of physical response. Finally, strategies for incorporating these factors into a perceptually adaptive real-time simulation of large numbers of visually similar objects are presented.

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.

For many systems that produce physically based animations, plausibility rather than accuracy is acceptable. We consider the problem of evaluating the visual quality of animations in which physical parameters have been distorted or degraded, either unavoidably due to real-time frame-rate requirements, or intentionally for aesthetic reasons. To date, no generic means of evaluating or predicting the fidelity, either physical or visual, of the dynamic events occurring in an animation exists. As a first step towards providing such a metric, we present a set of psychophysical experiments that established some thresholds for human sensitivity to dynamic anomalies, including angular, momentum and spatio-temporal distortions applied to simple animations depicting the elastic collision of two rigid objects. In addition to finding significant acceptance thresholds for these distortions under varying conditions, we identified some interesting biases that indicate non-symmetric responses to these distortions (e.g., expansion of the angle between postcollision trajectories was preferred to contraction and increases in velocity were preferred to decreases). Based on these results, we derived a set of probability functions that can be used to evaluate the visual fidelity of a physically based simulation. To illustrate how our results could be used, two simple case studies of simulation levels of detail and constrained dynamics are presented.

While many effective automatic surface simplification algorithms have been developed, they often produce poor approximations when a model is simplified to a very low level of detail. Furthermore, previous algorithms are not sensitive to semantic or highlevel meanings of models. In this paper, we present a user-guided approach for mesh simplification that aims to overcome such limitations. Our proposed method allows users to selectively control the relative importance of different surface regions and preserve various features through the imposition of geometric constraints. Using our system, users can produce perceptually improved approximations with very little effort.

this paper we introduce a new approach to realistic rendering at interactive rates on commodity graphics hardware. The approach uses efficient perceptual metrics within a decision theoretic framework to optimally order rendering operations, producing images of the highest visual quality within system constraints. We demonstrate the usefulness of this approach for various applications such as diffuse texture caching, environment map prioritization and radiosity mesh simplification. Although here we address the problem of realistic rendering at interactive rates, the perceptually-based decision theoretic methodology we introduce can be usefully applied in many areas of computer graphics

A number of successful tone mapping operators for contrast compression have been proposed due to the need to visualize high dynamic range (HDR) images on low dynamic range devices. They were inspired by fields as diverse as image processing, photographic practice, and modeling of the human visual systems (HVS). The variety of approaches calls for a systematic perceptual evaluation of their performance. We conduct a psychophysical experiment based on a direct comparison between the appearance of real-world scenes and HDR images of these scenes displayed on a low dynamic range monitor. In our experiment, HDR images are tone mapped by seven existing tone mapping operators. The primary interest of this psychophysical experiment is to assess the differences in how tone mapped images are perceived by human observers and to find out which attributes of image appearance account for these differences when tone mapped images are compared directly with their corresponding realworld scenes rather than with each other. The human subjects rate image naturalness, overall contrast, overall brightness, and detail reproduction in dark and bright image regions with respect to the corresponding real-world scene. The results indicate substantial differences in perception of images produced by individual tone mapping operators. We observe a clear distinction between global and local operators in favor of the latter, and we classify the tone mapping operators according to naturalness and appearance attributes. Keywords: high dynamic range (HDR) images, human visual systems (HVS), tone mapping, psychophysics, ANOVA, correlation, MANOVA, Mahalanobis distances. 1.

This paper presents a framework for handling and on-the-fly generation of levels of detail. The application directly controls the trade-off between the amount of resources to be used and the accuracy of the final images. The basis for this choice is an accuracy curve which explicates the trade-off. This curve is calculated and updated hierarchically, which makes it especially suited for use with a scene graph. Integration of the framework with VRML is described. Measurements on our prototype implementation show that target resource loads and accuracies can adequately be reached. Categories and Subject Descriptors I.3.3 [Computer Graphics]: Picture/Image Generation –

The perceived realism of a computer generated image depends on the accuracy of the modeling and illumination calculations, the limitations of the display device, and the way in which the Human Visual System processes this information. A real environment is unlikely to be pristine but will have accumulated dirt, dust and scratches from everyday use. Although human observers do not perhaps consciously take note of these phenomena, the absence of such features from the synthetic representation of that real scene may indeed affect the viewer's perceived realism of the virtual environment. This paper presents a series of psychophysical experiments to examine whether perceived realism of a virtual environment may be improved by adding textures artistically enhanced. Categories and Subject Descriptors

Figure 1: This image, when stared at for a while, can reveal four instances of a familiar figure. Two of the figures are easier to detect than the others. Locally there is little meaningful information, and we perceive the figures only when observing the whole figures. Emergence refers to the unique human ability to aggregate information from seemingly meaningless pieces, and to perceive a whole that is meaningful. This special skill of humans can constitute an effective scheme to tell humans and machines apart. This paper presents a synthesis technique to generate images of 3D objects that are detectable by humans, but difficult for an automatic algorithm to recognize. The technique allows generating an infinite number of images with emerging figures. Our algorithm is designed so that locally the synthesized images divulge little useful information or cues to assist any segmentation or recognition procedure. Therefore, as we demonstrate, computer vision algorithms are incapable of effectively processing such images. However, when a human observer is presented with an emergence image, synthesized using an object she is familiar with, the figure emerges when observed as a whole. We can control the difficulty level of perceiving the emergence effect through a limited set of parameters. A procedure that synthesizes emergence images can be an effective tool for exploring and understanding the factors affecting computer vision techniques. 1

Abstract—A mathematical model is presented for comparing geometric and image-based simplification methods. Geometric simplification reduces the number of polygons in the virtual object and image-based simplification replaces the object with an image. Our model integrates and extrapolates existing accuracy estimates, enabling the comparison of different simplification methods in order to choose the most efficient method in a given situation. The model compares data transfer and rendering load of the methods. Byte size and expected lifetime of simplifications are calculated as a function of the desired visual quality and the position and movement of the viewer. An example result is that, in typical viewing and rendering conditions and for objects with a radius in the order of one meter, imposter techniques can be used at viewing distances above 15 meters. Below that, simplified polygon objects are required and, below one meter distance, the full-resolution virtual object has to be rendered. An electronic version of the model is available on the web. Index Terms—Real-time rendering, dynamic geometry simplification, imposters, resource load, thin client, mathematical model. æ 1