Learning the methods of psychophysics is an essential part of training for perceptual experimentation, and hands-on experience is vital, but gaining this experience is difficult because good tools for learning are not available. The FechDeck is an ordinary deck of playing cards that has been modified to support learning the methods of psychophysics. Card backs are printed with noise patterns that span a range of densities. Faces are augmented with line segments arranged in “L” patterns. Jokers are printed with ruled faces and with backs that serve as standards. Instructions provided with the FechDeck allow users to perform threshold experiments using Fechner's methods of adjustment, limits, and constant stimuli; scaling experiments using Thurstone's ranking, paired comparison, and successive categories methods; and Stevens's magnitude estimation method. Spreadsheets provided with the deck support easy data entry and meaningful data analysis. An online repository supporting the FechDeck has been established to facilitate dissemination and to encourage open source development of the deck.

Rendering applications in design, manufacturing, ecommerce and other fields are used to simulate the appearance of objects and scenes. Fidelity with respect to appearance is often critical, and calculating global illumination (GI) is an important contributor to image fidelity; but it is expensive to compute. GI approximation methods, such as virtual point light (VPL) algorithms, are efficient, but they can induce image artifacts and distortions of object appearance. In this paper we systematically study the perceptual effects on image quality and material appearance of global illumination approximations made by VPL algorithms. In a series of psychophysical experiments we investigate the relationships between rendering parameters, object properties and image fidelity in a VPL renderer. Using the results of these experiments we analyze how VPL counts and energy clamping levels affect the visibility of image artifacts and distortions of material appearance, and show how object geometry and material properties modulate these effects. We find the ranges of these parameters that produce VPL renderings that are visually equivalent to reference renderings. Further we identify classes of shapes and materials that cannot be accurately rendered using VPL methods with limited resources. Using these findings we propose simple heuristics to guide visually equivalent and efficient rendering, and present a method for correcting energy losses in VPL renderings. This work provides a strong perceptual foundation for a popular and efficient class of GI algorithms.

Aggregates of individual objects, such as forests, crowds, and piles of fruit, are a common source of complexity in computer graphics scenes. When viewing an aggregate, observers attend less to individual objects and focus more on overall properties such as numerosity, variety, and arrangement. Paradoxically, rendering and modeling costs increase with aggregate complexity, exactly when observers are attending less to individual objects. In this paper we take some first steps to characterize the limits of visual coding of aggregates to efficiently represent their appearance in scenes. We describe psychophysical experiments that explore the roles played by the geometric and material properties of individual objects in observers' abilities to discriminate different aggregate collections. Based on these experiments we derive metrics to predict when two aggregates have the same appearance, even when composed of different objects. In a follow-up experiment we confirm that these metrics can be used to predict the appearance of a range of realistic aggregates. Finally, as a proof-of-concept we show how these new aggregate perception metrics can be applied to simplify scenes by allowing substitution of geometrically simpler aggregates for more complex ones without changing appearance.

Efficient, realistic rendering of complex scenes is one of the grand challenges in computer graphics. Perceptually based rendering addresses this challenge by taking advantage of the limits of human vision. However, existing methods, based on predicting visible image differences, are too conservative because some kinds of image differences do not matter to human observers. In this paper, we introduce the concept of visual equivalence , a new standard for image fidelity in graphics. Images are visually equivalent if they convey the same impressions of scene appearance, even if they are visibly different. To understand this phenomenon, we conduct a series of experiments that explore how object geometry, material, and illumination interact to provide information about appearance, and we characterize how two kinds of transformations on illumination maps (blurring and warping) affect these appearance attributes. We then derive visual equivalence predictors (VEPs): metrics for predicting when images rendered with transformed illumination maps will be visually equivalent to images rendered with reference maps. We also run a confirmatory study to validate the effectiveness of these VEPs for general scenes. Finally, we show how VEPs can be used to improve the efficiency of two rendering algorithms: Light-cuts and precomputed radiance transfer. This work represents some promising first steps towards developing perceptual metrics based on higher order aspects of visual coding.

In this paper we introduce a new perceptual metric for efficient, high quality, global illumination rendering. The metric is based on a rendering-by-components framework in which the direct, and indirect diffuse, glossy, and specular light transport paths are separately computed and then composited to produce an image. The metric predicts the perceptual importances of the computationally expensive indirect illumination components with respect to image quality. To develop the metric we conducted a series of psychophysical experiments in which we measured and modeled the perceptual importances of the components. An important property of this new metric is that it predicts component importances from inexpensive estimates of the reflectance properties of a scene, and therefore adds negligible overhead to the rendering process. This perceptual metric should enable the development of an important new class of efficient global-illumination rendering systems that can intelligently allocate limited computational resources, to provide high quality images at interactive rates.

In 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 classic photographic task is the mapping of the potentially high dynamic range of real world luminances to the low dynamic range of the photographic print. This tone reproduction problem is also faced by computer graphics practitioners who map digital images to a low dynamic range print or screen. The work presented in this paper leverages the time-tested techniques of photographic practice to develop a new tone reproduction operator. In particular, we use and extend the techniques developed by Ansel Adams to deal with digital images. The resulting algorithm is simple and produces good results for a wide variety of images.

In this paper we introduce a new light reflection model for image synthesis based on experimental studies of surface gloss perception. To develop the model, we've conducted two experiments that explore the relationships between the physical parameters used to describe the reflectance properties of glossy surfaces and the perceptual dimensions of glossy appearance. In the first experiment we use multidimensional scaling techniques to reveal the dimensionality of gloss perception for simulated painted surfaces. In the second experiment we use magnitude estimation methods to place metrics on these dimensions that relate changes in apparent gloss to variations in surface reflectance properties. We use the results of these experiments to rewrite the parameters of a physically-based light reflection model in perceptual terms. The result is a new psychophysically-based light reflection model where the dimensions of the model are perceptually meaningful, and variations along the dimensions are perceptually uniform. We demonstrate that the model can facilitate describing surface gloss in graphics rendering applications. This work represents a new methodology for developing light reflection models for image synthesis.

In this paper we develop a computational model of adaptation and spatial vision for realistic tone reproduction. The model is based on a multiscale representation of pattern, luminance, and color processing in the human visual system. We incorporate the model into a tone reproduction operator that maps the vast ranges of radiances found in real and synthetic scenes into the small fixed ranges available on conventional display devices such as CRT's and printers. The model allows the operator to address the two major problems in realistic tone reproduction: wide absolute range and high dynamic range scenes can be displayed; and the displayed images match our perceptions of the scenes at both threshold and suprathreshold levels to the degree possible given a particular display device. Although in this paper we apply our visual model to the tone reproduction problem, the model is general and can be usefully applied to image quality metrics, image compression methods, and perceptually-based...

In this paper we develop a computational model of visual masking based on psychophysical data.The model predicts how the presence of one visual pattern affects the detectability of another.The model allows us to choose texture patterns for computer graphics images that hide the effects of faceting, banding, aliasing, noise and other visual artifacts produced by sources of error in graphics algorithms.We demonstrate the utility of the model by choosing a texture pattern to mask faceting artifacts caused by polygonal tesselation of a flat-shaded curved surface.The model predicts how changes in the contrast, spatial frequency, and orientation of the texture pattern, or changes in the tesselation of the surface will alter the masking effect.The model is general and has uses in geometric modeling, realistic image synthesis, scientific visualization, image compression, and image-based rendering.

Our goal is to develop physically based lighting models and perceptually based rendering procedures for computer graphics that will produce synthetic images that are visually and measurably indistinguishable from real-world images. Fidelity of the physical simulation is of primary concern. Our research framework is subdivided into three sub-sections: the local light reflection model, the energy transport simulation, and the visual display algorithms. The first two subsections are physically based, and the last is perceptually based. We emphasize the comparisons between simulations and actual measurements, the difficulties encountered, and the need to utilize the vast amount of psychophysical research already conducted. Future research directions are enumerated. We hope that results of this research will help establish a more fundamental, scientific approach for future rendering algorithms. This presentation describes a chronology of past research in global illumination and how parts of our new system are currently being developed.

In this paper we develop a computational model of visual adaptation for realistic image synthesis based on psychophysical experiments. The model captures the changes in threshold visibility, color appearance, visual acuity, and sensitivity over time that are caused by the visual system's adaptation mechanisms. We use the model to display the results of global illumination simulations illuminated at intensities ranging from daylight down to starlight. The resulting images better capture the visual characteristics of scenes viewed over a wide range of illumination levels. Because the model is based on psychophysical data it can be used to predict the visibility and appearance of scene features. This allows the model to be used as the basis of perceptually-based error metrics for limiting the precision of global illumination computations. CR Categories and Subject Descriptors: I.3.0 [Computer Graphics]: General; I.3.6 [Computer Graphics]: Methodology and Techniques. Additional Key Words...