In computer graphics, illuminating a scene is a complex task, typically consisting of cycles of adjusting and rendering the scene to see the effects. We propose a technique for visualization of light as a tensor field via extracting its properties (i.e., intensity, direction, diffuseness) from (virtual) radiance measurements and showing these properties as a grid of shapes over a volume of a scene. Presented in the viewport, our visualizations give an understanding of the illumination conditions in the measured volume for both the local values and the global variations of light properties. Additionally, they allow quick inferences of the resulting visual appearance of (objects in) scenes without the need to render them. In our evaluation, observers performed at least as well using visualizations as using renderings when they were comparing illumination between parts of a scene and inferring the final appearance of objects in the measured volume. Therefore, the proposed visualizations are expected to help lighting artists by providing perceptually relevant information about the structure of the light field and flow in a scene.@en

In this article, we studied perception of a particular case of light fields that is characterized by a difference in its consistent structure between parts of a scene. In architectural lighting design, such a consistent structure in a part of a light field is called a light zone. First, we explored whether human observers are sensitive to light zones, that is, zones determined primarily by light flow differences, for a natural-looking scene. We found that observers were able to distinguish the light conditions between the zones. The results suggested an effect of light zones’ orientation. Therefore, in Experiment 2, we systematically examined how the orientation of light zones (left-right or front-back) with respect to a viewer influences light inferences in symmetric scenes. We found that observers are quite sensitive to the difference in the light flow of the light zones. In addition, we found that participants showed idiosyncratic behavior, especially for front-back-oriented light zones. Our findings show that observers are sensitive to differences in light field structure between two parts of a scene, which we call visual light zones.@en

Introduction: Human observers seem to robustly and effortlessly classify material properties, even when the optical input changes completely due to illumination changes. Previous research by Fleming et al. (2003) shows that the complexity of the illumination affects our judgments of glossiness. Here, we investigate the effects of both the nature of the illumination and the presence of context objects on the perceived glossiness of a reference object. Method: We compare perceived glossiness for complicated illumination (containing high frequency variations in the spatial luminance distribution, a bit like sunlight filtered through foliage), collimated illumination and diffuse illumination. As context objects, we use an arrangement of fruits, vegetables and vases that all either retained their original color and glossiness, were all spray painted matte gray, or were all spray painted specular gray. Participants viewed a gray reference object in that was either photographed in isolation or placed in a number of complex scenes, under three different illuminations. They matched the glossiness of a test object that was photographed in isolation on a matte background with collimated illumination to the glossiness of this reference object. Results: We found a huge underestimation of the glossiness of the object when the object was illuminated with a diffuse light source, compared to when the object was illuminated with a collimated light source, whereas glossiness was overestimated when illuminated with a highly complicated light source. In some participants, these biases were slightly reduced when specular or colored context objects were present. Conclusions: Results indicate that a richer environment, with complicated, more natural, illumination and a variety of different context materials, help us judge glossiness more accurately.@en

The appearance of objects in natural scenes is determined by their reflectance, their 3D texture, their shape and by the nature of the illumination. Results of previous experiments using computer generated images of spheres with different reflectance modes and under different canonical illuminations suggested that perception of reflectance mode and illumination are basically confounded. In the present study we investigate whether the conclusions from the experiments with simplified rendered spheres can be extended to ecologically valid images. We use two sets of photographs of real spheres, the first set is taken from the Dror Database [Dror et al. 2001], with simple reflectance modes but complex natural illumination (e.g. desklamp, lab, foodcourt). The second set is taken from the Utrecht Oranges Database [Pont and Koenderink 2003], with simple canonical illumination but material consisting of both reflectance and 3D texture differences (e.g. orange, golf ball, christmas decoration). We find that, although to a lesser extent, even in images of complex objects, perception of material and illumination are basically confounded. Overall, illumination and material are confounded most when we present rendered spheres that differ only in reflectance mode under simple canonical illumination conditions. Interestingly, adding complex natural illumination containing higher order angular frequencies helps to disambiguate this confound in material judgments, but not in illumination judgments. Most helpful was the addition of 3D texture.@en

Human observers are able to successfully infer direction and intensity of light from photographed scenes despite complex interactions between light, shape, and material. We investigate how well they are able to distinguish other low-level aspects of illumination, such as the diffuseness and the number of light sources. We use photographs of a teapot, an orange, and a tennis ball from the ALOI database (Geusebroek, Burghouts, & Smeulders, 2005) to create different illumination conditions, varying either in diffuseness of a single light source or in separation angle between two distinct light sources. Our observers were presented with all three objects; they indicated which object was illuminated differently from the other two. We record discrimination performance, reaction times, and eye fixations. We compare the data to a model that uses differences in image structure in same-object comparisons, and outcomes suggest that participants mostly rely on the information contained in cast shadows and highlights. The pattern of eye fixations confirms this, showing that after the first fixation, observers mostly fixate cast shadow areas. However, information in the highlights is rather salient, so it might be available from first fixation, making separate fixations are unnecessary.@en

We investigate the ability of human observers to judge the direction of illumination from image texture. Photographs of 61 real surfaces were used, taken from the Columbia-Utrecht Reflectance and Texture (Curet) database (http://www.cs.columbia.edu/CAVE/curet). All samples were normally viewed but obliquely illuminated, the elevation of the source being 22.5°, 45.0°, or 67.5°. The illumination was with a collimated, parallel beam. Stimuli were presented in random orientation, and observers had to judge both the elevation and the azimuth of the source. Observers judged the azimuth within approximately 15°, except for the fact that they committed random (with approximately 50% probability) sign flips (180° flips). Connected with this finding is the fact that observers judged the illumination to be from above rather than below in the overwhelming majority of cases, despite the fact that each case occurred with equal probability. The elevation of the illumination can be judged to some extent but is not far above chance level. The data are in good agreement with a simple model that bases the estimate of illumination direction on the second-order statistics of local luminance gradients. This locates the locus of the probable mechanism very early in the visual stream.@en

Human observers are sensitive to light properties such as the intensity, direction and diffuseness. We study how well they are able to estimate the light field (the structure of the net flux transport) in rooms, by empirical measurement and comparison of the physical and visual light fields. We made regularized measurements of the physical light field in a room under three light conditions with a custom-made cubic illuminance meter based on six Konica Minolta T-10MA sensors. Next, we photographed the room and conducted a psychophysical experiment, in which the observer’s task was to change the lighting (direction, intensity and ambient components) of a “probe” in order to make it appear like it belonged to the pictured scene. The probe, a white Lambertian sphere on a black monopod (defining the location of the probe in the scene), was superimposed on predetermined locations in the image. As a separate measure of the visual light field, the participants indicated the perceived (“subjective”) light source position on the extended scene pictures and described it in words. For each light condition we made reconstructions of light fields consisting of light vectors in a grid: physical from measurements, visual from observers’ settings on a probe, and simplified models of light fields with all vectors pointing to the subjective light source positions. Participants’ interpretations varied remarkably in position and number of the subjective light sources. Many of them were far from veridical. We made pairwise comparisons between light field reconstructions. For the most prominent case, with a visible light source, the average angular difference between visual and physical light vectors was 57 degrees, whereas between visual and simplified model for subjective light sources it was 29 degrees. The results suggest that, overall, the visual light field’s structure is simplified with respect to the physical one.@en

The appearance of objects depends on their material, shape, and on the illumination conditions. Conversely, object appearance provides us with cues about the illumination and the material. This so-called inverse problem is basically underdetermined and therefore we expect that material and illumination perception are confounded. To gain insight into the relevant mechanisms, we rendered a set of artificial spheres for vastly different canonical light fields and reflectance functions. We used four physics-based bidirectional reflectance distribution functions (BRDFs) representing glossy, pitted, velvety, and matte material. The six illumination conditions were collimated illumination from four directions, hemispherical diffuse illumination, and fully diffuse (Ganzfeld) illumination. In three sub-experiments we presented pairs of stimuli and asked human observers to judge whether the material was the same, whether the illumination was the same, and for a subset in which either the illumination or the material was the same to judge which of the two was constant. We found that observers made many errors in all sub-experiments. In experiment 2 the illumination direction was chosen at random. Using an interactive interface, we asked human observers to match the illumination direction of a sphere of one of the four materials with that of a Lambertian sphere. We found systematical material-dependent deviations from veridical performance. Theoretical analysis of the radiance patterns suggests that judgments were based mainly on the position of the shadow edge. In conclusion, we found no evidence for 'material constancy' for perception of smooth rendered spheres despite vast quantitative and qualitative differences in illumination and in BRDF between the stimuli. Although human observers demonstrated some 'illumination constancy', they made systematic errors depending on the material reflectance, suggesting that they used mainly the location of the shadow edge. Our results suggest that material perception and light-field perception are basically confounded.@en

Image texture due to 3D surface corrugations ("3D texture") differs fundamentally from image texture due to pigmentation variations of a smooth surface ("flat texture"). Flat texture yields no information concerning the way the surface is illuminated, whereas 3D texture is highly dependent upon the illumination. Question: Is the human observer able to perceive the illumination direction from 3D texture? Method: In order to address this question we extracted over sixty 3D textures due to natural materials from the Curet database. Fiducial illumination directions were 22.5°, 45° and 67.5° from the normal direction, all viewing directions were normal. The samples were clipped to circular discs and were randomly rotated in the picture plane. Observers indicated perceived illumination direction by way of an indicator panel showing a hemispherical boss on a plane, viewed normally to the plane. The simulated illumination direction was under the observer's control. Five observers viewed all samples in six different orientations. Result: We find that the azimuth of the illumination direction can be perceived quite veridically except for the fact that 180° confusions are frequent. The elevation cannot be perceived with great certainty (deviations up to 45° occurring frequently) though the increase of perceived elevation with true elevation is significant. We find a number of interesting variations on this pattern that depend critically upon the type of texture.@en