Predicting environment illumination effects on material appearance (original) (raw)

The perception of simulated materials

ACM SIGGRAPH 2008 classes, 2008

Numerically modeling the interaction of light with materials is an essential step in generating realistic synthetic images. While there have been many studies of how people perceive physical materials, very little work has been done that facilitates efficient numerical modeling. Perceptual experiments and guidelines are needed for material measurement, specification and rendering. For measurement, many devices and methods have been developed for capturing spectral, directional and spatial variations of light/material interactions, but no guidelines exist for the accuracy required. For specification, only very preliminary work has been done to find meaningful parameters for users to search for and to select materials in software systems. For rendering, insight is needed on the perceptual impact of material models when combined with global illumination methods.

User study of viewing and illumination dependent material appearance

Our research focuses on a way how people view real materials with respect to their orientation as well as illumination direction. We performed user study with fifteen naive subjects using novel interactive stimuli where subjects could arbitrarily change orientations of planar surface and directional illumination. Seven real materials were represented by means of illumination and view dependent textures. The study comprised two experiments, free-view and task-oriented, and user behavior across different samples together with their answers to questionnaire were recorded and analysed.

The influence of lighting on visual perception of material qualities

Proceedings of SPIE, 2015

We studied whether lighting influences the visual perception of material scattering qualities. To this aim we made an interface or "material probe", called MatMix 1.0, in which we used optical mixing of four canonical material modes. The appearance of a 3D object could be adjusted by interactively adjusting the weights of the four material components in the probe. This probe was used in a matching experiment in which we compared material perception under generic office lighting with that under three canonical lighting conditions. For the canonical materials, we selected matte, velvety, specular and glittery, representing diffuse, asperity, forward, and specular micro facet scattering modes. For the canonical lightings, we selected ambient, focus and brilliance lighting modes. In our matching experiment, observers were asked to change the appearance of the probe so that the material qualities of the probe matched that of the stimuli. From the matching results, we found that our brilliance lighting brought out the glossiness of our stimuli and our focus lighting brought out the velvetiness of our stimuli most similarly to office lighting. We conclude that the influence of lighting on material perception is material-dependent.

Statistical Analysis and Psychological Evaluation of Surfaces under Various Illuminations

Applied Mechanics and Materials, 2010

Perceptions of image surface are very challenging work for computer vision. Human can amazingly expert at recognizing the reflective properties of surfaces of various materials which a robot can not do easily so far. Smoothly we can differentiate a shiny metallic sphere from the plastic sphere of similar dimensions and structure. In this paper, various image surfaces are analyzed according to various image statistics for robot vision systems. Identification of synonymous objects under various real-world illumination or other environments are very daunting task. However, this is very challenging and crucial for machine vision systems. Both statistical analyses and human evaluation by various subjects under rigorous illumination conditions, we find significant improvement in our analysis and emphasis the importance of statistical evaluation of surfaces for computer vision. Our findings clearly demonstrate that skewness has direct resemblance with the surface glossiness-level. Intensit...

Evaluating physical and rendered material appearance

The Visual Computer, 2018

Many representations and rendering techniques have been proposed for presenting material appearance in computer graphics. One outstanding problem is evaluating their accuracy. In this paper, we propose assessing accuracy by comparing human judgements of material attributes made when viewing a computer graphics rendering to those made when viewing a physical sample of the same material. We demonstrate this approach using 16 diverse physical material samples distributed to researchers at the MAM 2014 workshop. We performed two psychophysical experiments. In the first experiment we examined how consistently subjects rate a set of twelve visual, tactile and subjective attributes of individual physical material specimens. In the second experiment, we asked subjects to assess the same attributes for identical materials rendered as BTFs under point-light and environment illuminations. By analyzing obtained data, we identified which material attributes and material types are judged consistently and to what extent the computer graphics representation conveyed the experience of viewing physical material appearance.

A Technique for Comparing Human Visual Responses with a Mathematical Model for Lightness

Optometry and Vision Science, 1970

This paper reports a technique for comparing the human visual responses with lightness predictions made by a mathematical model. The human visual responses are determined by ha\'ing a number of observers compare the lightnesses in a Test Display with those in a Standard Display. The mathematical model's predictions are made by processing numbers that are identical to the luminances in the Test Display. These predictions are then scaled relati"e to the Standard Lightness Display used by human observers. Methods of analyzing the results are discussed, as well as a "ariety of :;ituations that can be used co establish whether a particular model can be considered a general model for lightness. The purpose of this paper is to describe a technique for comparing the human lightness response with a mathematical model of that mechanism. Since lightness is in itself a complex, diverse problem, we feel that it is necessary to test any model for lightn~~ in a variety of situations. Our method for comparing observers' results with any mathematical model's results for a variety of test situations will constitute the scope of this paper. Lightness 1 , 2, 3, 4 is the family of sensations from white to black that a person sees. Lightness is the output of a biological system. It is a sensation. There is no physical definition for lightness because it is not necessarily related to a physical quantity of light from a point. either in radiometric terms or photometric terms. Although it is commonly believed that there is a simple relationship between the amount of light coming from an object and how light or dark that object appears, there are many experiments that contradict that belief5, 6,7. As a particular example. let us study an experiment by Land. A display called a McCann 8 Mondrian was made of various white, gray. and black papers. The papers were arranged so that the surround around each paper was arbitrary, multiple and variegated. The surround was arbitrary because there were no consistent patterns such as only low reflectance papers around hig'h reflectance papers. The surround was multiple because there were many different papers around each

Effects of light map orientation and shape on the visual perception of canonical materials

Journal of Vision, 2020

We previously presented a systematic optics-based canonical approach to test material-lighting interactions in their full natural ecology, combining canonical material and lighting modes. Analyzing the power of the spherical harmonics components of the lighting allowed us to predict the lighting effects on material perception for generic natural illumination environments. To further understand how material properties can be brought out or communicated visually, in the current study, we tested whether and how light map orientation and shape affect these interactions in a rating experiment: For combinations of four materials, three shapes, and three light maps, we rotated the light maps in 15 different configurations. For the velvety objects, there were main and interaction effects of lighting and light map orientation. The velvety ratings decreased when the main light source was coming from the back of the objects. For the specular objects, there were main and interaction effects of lighting and shape. The specular ratings increased when the environment in the specular reflections was clearly visible in the stimuli. For the glittery objects, there were main and interaction effects of shape and light map orientation. The glittery ratings correlated with the coverage of the glitter reflections as the shape and light map orientation varied. For the matte objects, results were robust across all conditions. Last, we propose combining the canonical modes approach with so-called importance maps to analyze the appearance features of the proximal stimulus, the image, in contradistinction to the physical parameters as an approach for optimization of material communication.

The Effect of Texture on Brightness Perception in Simulated Scenes

LEUKOS, 2019

It is known that there is a black-white asymmetry in the psychophysical response; this is such that decrements are represented in the visual system by a larger magnitude than increments, that have an equal-magnitude deviation from the background. One interesting prediction arises from this black-white asymmetry that is: an homogeneously textured surface in which each dot belongs to a range of grays, and whose mean luminance is L, will be perceived as darker than a uniform surface with the same luminance L. We propose to explore this effect and analyze its potential consequences on the brightness perception of surfaces in illuminated scenes. For this purpose, we performed two experiments: in the first one, we showed that the texture biases the perception of surface brightness. In the second one, we showed, by testing the effect on simulated 3D realistic scenes, that textured walls are perceived as darker than identically painted walls with soft finish.

Image statistics for surface reflectance perception

Journal of the Optical Society of America A, 2008

Human observers can distinguish the albedo of real-world surfaces even when the surfaces are viewed in isolation, contrary to the Gelb effect. We sought to measure this ability and to understand the cues that might underlie it. We took photographs of complex surfaces such as stucco and asked observers to judge their diffuse reflectance by comparing them to a physical Munsell scale. Their judgments, while imperfect, were highly correlated with the true reflectance. The judgments were also highly correlated with certain image statistics, such as moment and percentile statistics of the luminance and subband histograms. When we digitally manipulated these statistics in an image, human judgments were correspondingly altered. Moreover, linear combinations of such statistics allow a machine vision system (operating within the constrained world of single surfaces) to estimate albedo with an accuracy similar to that of human observers. Taken together, these results indicate that some simple image statistics have a strong influence on the judgment of surface reflectance.