Effect of Pictorial Depth Cues, Binocular Disparity Cues and Motion Parallax Depth Cues on Lightness Perception in Three-Dimensional Virtual Scenes (original) (raw)
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Modeling lightness perception - Another point of view
2014
In a recent note, Brill and Carter propose to revisit the centuries-old disagreement over the relationship between stimuli and perceived lightness or brightness and the mathematical model that best represents it. Here, the answer is offered that the only way to resolve this matter is empirically, with controlled experiments of different kinds that establish statistically meaningful and replicated data for a given set of test conditions and methodology. Given the fact that surround lightness has a very significant effect on the results, including the crispening effect, a model can only be valid for a limited set of conditions, and the likely outcome is multiple models or models with multiple variables.
2010
Architects often use two-dimensional media to represent, visualise, and study the three-dimensional qualities of un-built spaces. Knowledge of pictorial cues is a powerful design tool that can be used to enhance the spatial qualities of built environments. This paper draws from the recent developments in computer graphics (physically based renderings and perceptually based tone mapping techniques) and dem- onstrates the utilisation of a computational framework to generate pic- torial spaces that can mimic perceptual reality. Computer simulation and psychophysical research methodologies are employed to examine the relationship between the lighting patterns introduced by architec- tural confi gurations and their impacts on depth perception. The research demonstrates that physically and perceptually based renderings can be used to study depth perception; and luminance contrast in an archi- tectural scene is an effective pictorial cue that increases the perceived spatial depth.
CAADRIA proceedings
Architects often use two-dimensional media to represent, visualise, and study the three-dimensional qualities of un-built spaces. Knowledge of pictorial cues is a powerful design tool that can be used to enhance the spatial qualities of built environments. This paper draws from the recent developments in computer graphics (physically based renderings and perceptually based tone mapping techniques) and demonstrates the utilisation of a computational framework to generate pictorial spaces that can mimic perceptual reality. Computer simulation and psychophysical research methodologies are employed to examine the relationship between the lighting patterns introduced by architectural confi gurations and their impacts on depth perception. The research demonstrates that physically and perceptually based renderings can be used to study depth perception; and luminance contrast in an architectural scene is an effective pictorial cue that increases the perceived spatial depth.
Lightness perception can be affected by surface curvature from stereopsis
Perception, 1994
It is demonstrated that lightness perception can be affected by shape from stereopsis. The starting point was a report by Knill and Kersten that the perceived lightness of a monocularly viewed surface can be affected by outline-contour cues indicating that the surface is threedimensional (3-D). In that study stimuli consisted of two equally sized abutting regions each having the same vertical linear-intensity ramp, so that the horizontal abutting boundary of the two patches created a sharp change in intensity. When this version of the Craik-O'Brien -Cornsweet stimulus has a rectangular outline, it exhibits the standard simultaneous contrast illusion: equivalent patches in the top and bottom regions appear to have different brightness despite having the same luminance. Knill and Kersten replicated this phenomenon with stimuli whose outline-contour cues were consistent with a flat (planar) surface. They found, however, that the illusion was greatly reduced in stimuli with outlines consistent with two abutting 3-D quarter cylinders, for which equivalent regions in the two halves appeared of similar lightness. Knill and Kersten interpreted this effect in terms of surface-lightness computations that took into account 3-D surface shape to achieve an integrated interpretation of the luminance and shape data. In the present report three experiments are described for which these earlier findings were taken as the starting point. In the first experiment the results were replicated by the use of a different methodology. In the second experiment it was shown that shape-fromstereo can produce similar effects on lightness perception to that caused by shape-from-contour. Real 3-D objects with curved surfaces, luminance profiles of the Knill and Kersten type, and carefully controlled outline-contour cues were used so that the objects appeared flat when viewed monocularly but curved in 3-D when seen binocularly. The third experiment was a control confirming that the stereo effect was not simply due to differences caused by monocular versus binocular viewing. It is concluded that the human visual system uses stereo cues, as well as outline-contour cues, in the interpretation of luminance data to recover surface lightness.
Lightness constancy and illumination discounting
Attention Perception & Psychophysics
Contrary to the implication of the term “lightness constancy”, asymmetric lightness matching has never been found to be perfect unless the scene is highly articulated (i.e., contains a number of different reflectances). Also, lightness constancy has been found to vary for different observers, and an effect of instruction (lightness vs. brightness) has been reported. The elusiveness of lightness constancy presents a great challenge to visual science; we revisit these issues in the following experiment, which involved 44 observers in total. The stimuli consisted of a large sheet of black paper with a rectangular spotlight projected onto the lower half and 40 squares of various shades of grey printed on the upper half. The luminance ratio at the edge of the spotlight was 25, while that of the squares varied from 2 to 16. Three different instructions were given to observers: They were asked to find a square in the upper half that (i) looked as if it was made of the same paper as that on which the spotlight fell (lightness match), (ii) had the same luminance contrast as the spotlight edge (contrast match), or (iii) had the same brightness as the spotlight (brightness match). Observers made 10 matches of each of the three types. Great interindividual variability was found for all three types of matches. In particular, the individual Brunswik ratios were found to vary over a broad range (from .47 to .85). That is, lightness matches were found to be far from veridical. Contrast matches were also found to be inaccurate, being on average, underestimated by a factor of 3.4. Articulation was found to essentially affect not only lightness, but contrast and brightness matches as well. No difference was found between the lightness and luminance contrast matches. While the brightness matches significantly differed from the other matches, the difference was small. Furthermore, the brightness matches were found to be subject to the same interindividual variability and the same effect of articulation. This leads to the conclusion that inexperienced observers are unable to estimate both the brightness and the luminance contrast of the light reflected from real objects lit by real lights. None of our observers perceived illumination edges purely as illumination edges: A partial Gelb effect (“partial illumination discounting”) always took place. The lightness inconstancy in our experiment resulted from this partial illumination discounting. We propose an account of our results based on the two-dimensionality of achromatic colour. We argue that large interindividual variations and the effect of articulation are caused by the large ambiguity of luminance ratios in the stimulus displays used in laboratory conditions.
Lightness perception in simple images: testing the anchoring rules
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One approach toward understanding how vision computes surface lightness is to first determine what principles govern lightness in simple stimuli and then test whether these hold for more complex stimuli. Gilchrist (2006) proposed that in the simplest images that produce the experience of a surface (two surfaces differing in luminance that fill the entire visual field) lightness can be predicted based on two anchoring rules: the highest luminance rule and the area rule, plus a scale normalization. To test whether these anchoring rules hold when critical features of the stimuli are varied, we probed lightness in simple stimuli, painted onto the inside of hemispheric domes viewed under diffuse lighting. We find that although the highest luminance surface appears nearly white across a large variation in illumination (as predicted by the highest luminance rule), its lightness tends to increase as its luminance increases. This effect is small relative to the size of the overall luminance ...
The Influence of Physical Illumination on Lightness Perception in Simultaneous Contrast Displays
i-Perception
Three experiments investigated the role of physical illumination on lightness perception in simultaneous lightness contrast (SLC). Four configurations were employed: the classic textbook version of the illusion and three configurations that produced either enhanced or reduced SLC. Experiment 1 tested the effect of ambient illumination on lightness perception. It simulated very dark environmental conditions that nevertheless still allowed perception of different shades of gray. Experiment 2 tested the effect of the intensity of Gelb lighting on lightness perception. Experiment 3 presented two conditions that integrated illumination conditions from Experiments 1 and 2. Our results demonstrated an illumination effect on both lightness matching and perceived SLC contrast: As the intensity of illumination increased, the target on the black background appeared lighter, while the target on the white background was little affected. We hypothesize the existence of two illumination ranges tha...
Depth Perception as a Function of Lighting, Time, and Spatiality
Illuminating Engineering Society (IES) …, 2009
Perceptual qualities of luminous environment change based on spatiality, time, and observer. This paper focuses on the complex interrelationships between architectural configurations, luminance distribution patterns, and the perception of spatial depth. A ...
The Dynamic Range of Human Lightness Perception
Current Biology, 2011
Natural viewing challenges the visual system with images that have a dynamic range of light intensity (luminance) that can approach 1,000,000:1 and that often exceeds 10,000:1 [1, 2]. The range of perceived surface reflectance (lightness), however, can be well-approximated by the Munsell matte neutral scale (N 2.0/ to N 9.5/), consisting of surfaces whose reflectance varies by about 30:1. Thus, the visual system, must map a large range of surface luminance onto a much smaller range of surface lightness. We measured this mapping in images with a dynamic range close to that of natural images. We studied simple images that lacked segmentation cues that would indicate multiple regions of illumination. We found a remarkable degree of compression: at a single image location, a stimulus luminance range of 5905:1 can be mapped onto an extended lightness scale that has a reflectance range of 100:1. We characterized how the luminance-tolightness mapping changes with stimulus context. Our data rule out theories that predict perceived lightness from luminance ratios or Weber contrast. A mechanistic model connects our data to theories of adaptation and provides insight about how the underlying visual response varies with context.
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Space perception is the ability to estimate the three-dimensional layout of our environment from the arrangement of individual objects, their location and size. While estimating every distance in the three-dimensional environment, the human visual system uses a number of physical cues and depth perception can be affected by a variety of factors; reflectance, colour, and texture. The main purpose of this study is to understand the effect of chromaticity combinations on depth perception. A forced-choice paired comparison test was used to evaluate distance differences between colour combinations created by chromatic light in background and coloured objects in front. The experiments indicated perceptual variations in-depth assessments between different participants, which needed to be taken into consideration. The findings suggest a significant effect of some colour combinations on depth perception.