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We used a novel probe disk technique to test for the existence of functional frames of reference for lightness perception in complex images. Thirteen identical gray disks were electronically pasted into the photograph Trastevere, which shows two large regions of sunlight and shadow. Observers matched the lightness of each disk with a Munsell scale. The data revealed a framework effect. That is, lightness differences within either the sunlight or shadow region were small relative to the pronounced step function at the framework boundary. Additional experiments testing the perceived embeddedness of the disks showed that the framework effect was increased when disk size and shape were altered to conform to the perspective shown in the photograph and when the disks were blurred slightly to conform to the graininess of the photograph. The effect was further increased when the photograph was viewed through a pinhole and when the disks were presented one by one. The effect was reduced when paper disks of equal luminance and visual angle were pasted onto the glass front of the CRT screen. When the sunlight framework was covered with black paper, the remained disks within the shadow region appeared white, as predicted by the anchoring theory (A. Gilchrist, 2006).

How do human observers estimate the location, form, and color of objects? Accurate estimation is challenging because the light arriving at the eyes depends not only on object properties, but also on the spectra and spatial layout of the light sources (Nassau, 1983; Foley et al., 1990). How well the visual system separates illuminant and object properties to achieve a stable representation has traditionally been studied under the rubric of color and lightness constancy. Most previous work used very simple stimuli, typically a few diffusely illuminated surfaces arranged perpendicular to the line of sight. Over the past several years, however, there has been an evident increase of interest in expanding the conceptualization of this area to incorporate effects that emerge only for complex, typically three-dimensional, scenes. The current issue features papers that represent various manifestations of this interest. One line of research investigates how the three-dimensional layout of a scene affects the perception of lightness and color. Although the current work has long-standing antecedents (e.g. Mach, 1886/1959; Hochberg and Beck, 1954; Gilchrist, 1980), methodological advances in i) experimentation with real illuminated objects (e.g. Brainard et. al, 1987; Rutherford and Brainard, 2002; Ripamonti et al., 2004; Robilotto and Zaidi, 2004), ii) the use of sophisticated graphics simulations (e.g. Yang and Maloney, 1999; Fleming, Dror, & Adelson, 2003; Boyaci, Maloney, & Hersh, 2003; Delahunt and Brainard, 2004), iii) the design of hybrid systems that combine real objects with image-based graphics and video projection (Ling and Hurlbert, 2004), and iv) psychophysical procedures (Maloney and Yang, 2003; Obein, Knoblauch, & Vienot, 2004) have opened the door for systematic exploration of a wider range of phenomena. Recent papers include work on how well vision compensates for changes in surface orientation (Boyaci et al., 2003; Ripamonti et al., 2004), how effectively it discounts inter-reflections among nearby surfaces (Bloj, Kersten, & Hurlbert, 1999; Doerschner, Boyaci, & Maloney, 2004; Delahunt and Brainard, 2004), and how the visual system effectively estimates the spectral properties and spatial layout of the illuminant in three-dimensional scenes (Kraft & Brainard, 1999; Yang & Maloney, 1999; Boyaci, Maloney, & Hersh, 2003; Bloj et al., 2004; Boyaci, Doerschner, & Maloney, 2004; Khang and Zaidi, 2004). The second thread that leads to papers in the current issue is a focus on the functional utility of color and lightness perception -- the idea that these percepts inform us about the properties of objects rather than those of light spectra. This focus resulted in a renaissance of research in color constancy over the past two decades, with particular progress being made in the development of computational models that explore how, in principle, object surface properties can be estimated from image data. As with the experimental lines, early work focused on simple scene geometries (for reviews see Hurlbert, 1998; Maloney, 1999) but consideration has recently expanded to three-dimensional configurations (Adelson and Pentland, 1996; Yang and Maloney, 1999; Bell and Freeman, 2001; Dror, Willsky, & Adelson, 2004) Of particular interest has been the elaboration of purely computational formulations into parametric models of human performance (e.g. Brainard Brunt, & Speigle, 1997; Brainard Kraft, & Longere, 2003; Boyaci et al., 2003; Doerschner et al., 2004; Boyaci et al., 2004; Bloj et al., 2004), tests of how well the visual system exploits image information identified in computational studies (Yang and Maloney, 2001; Delahunt and Brainard, 2004; Smithson and Zaidi, 2004), investigations of how well the visual system recovers perceptual correlates of material properties other than diffuse surface reflectance, such as gloss and translucency (Lu, Koenderink, & Kappers, 2000; Fleming et al., 2003; Pont & Koenderink, 2003; Obein et al., 2004), as well as how geometric aspects of surface reflectance interact with the perception of shape (Fleming et al., 2003).

When judging optical properties of a translucent object, humans often look at sharp geometric features such as edges and thin parts. Analysis of the physics of light transport shows that these sharp geometries are necessary for scientific imaging systems to be able to accurately measure the underlying material optical properties. In this paper, we examine whether human perception of translucency is likewise affected by the presence of sharp geometry, by confounding our perceptual inferences about an object’s optical properties. We employ physically accurate simulations to create visual stimuli of translucent materials with varying shapes and optical properties under different illuminations. We then use these stimuli in psychophysical experiments, where human observers are asked to match an image of a target object by adjusting the material parameters of a match object with different geometric sharpness, lighting geometry, and 3D geometry. We find that the level of geometric sharpness significantly affects perceived translucency by the observers. These findings generalize across a few illuminations and object shapes. Our results suggest that the perceived translucency of an object depends on both the underlying material optical parameters and 3D shape. We also conduct analyses using computational metrics including (luminance-normalized) L2, structural similarity index (SSIM), and Michelson contrast. We find that these image metrics cannot predict perceptual results, suggesting low level image cues are not sufficient to explain our results.

Our capacity to become aware of visual stimuli is limited. Investigating these limits, Cohen et al. (2015, Journal of Cognitive Neuroscience) found that certain object categories (e.g., faces) were more effective in blocking awareness of other categories (e.g., buildings) than other combinations (e.g., cars/chairs) in the continuous flash suppression (CFS) task. They also found that more category-pair representational similarity in higher visual cortex was related to longer category-pair breakthrough times suggesting a high-level representational architecture bottleneck for visual awareness. As the cortical representations of hands and tools overlap, these categories are ideal to test this further. We conducted CFS experiments and predicted longer breakthrough times for hands/tools compared to other pairs. In contrast to these predictions, participants were generally faster at detecting targets masked by hands or tools compared to other mask categories when giving manual (Experiment 1) or vocal responses (Experiment 2). Furthermore, we found the same inefficient mask effect for hands in the context of the categories used by Cohen et al. (2015) and found a similar behavioural pattern as the original paper (Experiment 3). Exploring potential low-level explanations, we found that the category average for edges (e.g. hands have less detail compared to cars) was the best predictor for the data. However, these category-specific image characteristics could not completely account for the Cohen et al. (2015) category pattern or for the hand/tool effects. Thus, several low- and high-level object category-specific limits for visual awareness are plausible and more investigations are needed to further tease these apart.

Fast and accurate recognition of both the identities and positions of objects in visual space is critical to deciphering visual environments. Studies in both humans and nonhuman primates have demonstrated that neural populations in ventral temporal visual areas are jointly tuned to both the form and position of objects, allowing information about the identities of objects to be "tagged" with their positions. Because not all behaviors demand that the identities of objects be associated with position information with equal precision, however, the present study asked whether the spatial tuning of form-encoding populations in the human lateral occipital complex (LOC) is sculpted by task demands. Subjects were scanned using functional magnetic resonance imaging while viewing matches of the game Rock, Paper, Scissors played with exemplar pairs from those categories. Subjects first performed a repetition-detection task that depended on object form but not position; subsequently, subjects viewed the same stimuli while determining the position of each pair's "winner," a task that depended upon the conjunction of object form and position. Compared to data from the initial scan, multivoxel activity patterns evoked in the lateral occipital (LO) subdivision of LOC while subjects judged winners showed enhanced sensitivity to the relative positions of objects in pairs. Although superficially consistent with dynamic position tuning, this effect appears to be attributable to an accompanying task-dependent improvement in the sensitivity of LO populations to object form. The results thus suggest that the spatial tuning of form-encoding populations in LO does not depend upon the precision of spatial information demanded by a task.

The human visual system has a remarkable ability to perceive three-dimensional (3-D) surface shape from shading and specular reflections. This paper presents two experiments that examined the perception of local qualitative shape under various conditions. Surfaces were rendered using standard computer graphics models of matte, glossy, and mirror reflectance and were viewed from a small oblique angle to avoid occluding contour shape cues. The subjects' task was to judge whether a marked point on each surface lay on a local hill or valley. In the first experiment, performance was lower for glossy surfaces than matte surfaces, which is contrary to findings in previous studies of quantitative shape. For mirror surfaces, performance was high despite the absence of occluding contours, and performance was increased when the environment map was brighter in the upper hemisphere as in a natural environment. The second experiment examined how subjects resolve a depth-reversal shape ambiguity where surfaces can be either upward or downward facing. An upward-facing surface prior that is known to exist for matte surfaces was also found to exist for glossy and mirror surfaces. Subjects relied entirely on this prior to resolve the depth-reversal ambiguity for matte and glossy surfaces, but relied on perspective cues as well for mirror surfaces.

In this paper, we propose to model the edge information contained in natural scenes as points in the 3D space of positions and orientations. This space is equipped with a strong geometrical structure and it is identified as the rototranslation group. In this space, we compute a histogram of co-occurrence of edges from a database of natural images and show that it can be interpreted as a probability density function, expressed by the fundamental solution of a suitable Fokker–Planck equation defined in the 3D structured space. Both estimated statistics and model predictions are reconsidered and compared with the partial gestalt association fields proposed by D. J. Field, A. Hayes, and R. F. Hess (1993). Finally, parametric identification allows to estimate the variance of the co-occurrence random process in natural images.

Identifying the visual cues that determine relative depth across an image contour (i.e., figure-ground organization) is a central problem of vision science. In this paper, we compare flat cues to figure-ground organization with the recently discovered cue of extremal edges (EEs), which arise when opaque convex surfaces smoothly curve to partly occlude themselves. The present results show that EEs are very powerful pictorial cues to relative depth across an edge, almost entirely dominating the well-known figure-ground cues of relative size, convexity, shape familiarity, and surroundedness. These results demonstrate that natural shading and texture gradients in an image provide important information about figure-ground organization that has largely been overlooked in the past 75 years of research on this topic.

Figure-ground assignment to a contour is a fundamental stage in visual processing. The current paper introduces a novel, highly general dynamic cue to figure-ground assignment: "Convex Motion." Across six experiments, subjects showed a strong preference to assign figure and ground to a dynamically deforming contour such that the moving contour segment was convex rather than concave. Experiments 1 and 2 established the preference across two different kinds of deformational motion. Additional experiments determined that this preference was not due to fixation (Experiment 3) or attentional mechanisms (Experiment 4). Experiment 5 found a similar, but reduced bias for rigid-as opposed to deformational-motion, and Experiment 6 demonstrated that the phenomenon depends on the global motion of the effected contour. An explanation of this phenomenon is presented on the basis of typical natural deformational motion, which tends to involve convex contour projections that contain regions consisting of physical "matter," as opposed to concave contour indentations that contain empty space. These results highlight the fundamental relationship between figure and ground, perceived shape, and the inferred physical properties of an object.

This paper describes a new model for human visual classification that enables the recovery of image features that explain performance on different visual classification tasks. Unlike some common methods, this algorithm does not explain performance with a single linear classifier operating on raw image pixels. Instead, it models classification as the result of combining the output of multiple feature detectors. This approach extracts more information about human visual classification than has been previously possible with other methods and provides a foundation for further exploration.

The relationship between image features and scene structure is central to the study of human visual perception and computer vision, but many of the specifics of real-world layout perception remain unknown. We do not know which image features are relevant to perceiving layout properties, or whether those features provide the same information for every type of image. Furthermore, we do not know the spatial resolutions required for perceiving different properties. This paper describes an experiment and a computational model that provides new insights on these issues. Humans perceive the global spatial layout properties such as dominant depth, openness, and perspective, from a single image. This work describes an algorithm that reliably predicts human layout judgments. This model’s predictions are general, not specifi ct o the observers it trained on. Analysis reveals that the optimal spatial resolutions for determining layout vary with the content of the space and the property being estimated. Openness is best estimated at high resolution, depth is best estimated at medium resolution, and perspective is best estimated at low resolution. Given the reliability and simplicity of estimating the global layout of real-world environments, this model could help resolve perceptual ambiguities encountered by more detailed scene reconstruction schemas.

This paper reports psychophysical and modelling results concerning the contour-detection paradigm of D. J. Field, A. Hayes, and R. F. Hess (1993). We measured psychophysically the maximum tolerable contour curvature (path angle) as a function of contour length. We compared these data to the predictions of an association field (D. J. Field et al., 1993) model based on the relative positions and mutual orientations of nearby elements and to models that explicitly link adjacent elements into chains and characterize each chain by its sequence of contour bends. For every stimulus, a large set of chains is produced and the target identified as the chain with the lowest maximum bend. We tested two different types of linking process: isotropic (linking one element to any other nearby) and anisotropic (linking one element to any others nearby along the orientation of its axis). All of these models can account for our data. Moreover, we show that the pattern of results due to path angle is principally a product of the distribution of spurious contours in the randomly oriented background. Given that some of the models do not embody constraints of orientation relationships between linked elements, this finding shows the importance for early vision in deciding which local elements are to be associated.

We applied the thin-fat Kanizsa shape discrimination task invented by D. L. Ringach and R. Shapley (1996) to study perceptual completion by measuring whether the discrimination was more accurate for illusory than for occluded shapes. Differently from Ringach and Shapley, we tested naive observers with stereoscopic displays. Discrimination was consistently more accurate for illusory than for occluded shapes under a variety of stimulus conditions. However, the absolute performance was worse than Ringach and Shapley's experienced observers, who discriminated illusory and occluded shapes equally well. When our naive observers were trained, their performance approached that in Ringach and Shapley, and their performance difference diminished between the illusory and occluded. The more precise discrimination of the illusory shapes by untrained observers is consistent with the subjective impression that illusory contours appear clearer and positionally better defined. This makes sense from the perspective of Bayesian decision theory: the location of an illusory contour that is closer to an observer might be more important than an occluded contour, and hence obligatorily represented more precisely. We conclude the paper by discussing implications of our results on the current debate on mechanisms of perceptual completion (M. K. Albert, 2007; B. L. Anderson, 2007; P. J. Kellman, P. Garrigan, T. F. Shipley, & B. P. Keane, 2007).

Translucency is an important aspect of material appearance. To some extent, humans are able to estimate translucency in a consistent way across different shapes and lighting conditions, i.e., to exhibit translucency constancy. However, Fleming and Bülthoff (2005) have shown that that there can be large failures of constancy, with lighting direction playing an important role. In this paper, we explore the interaction of shape, illumination, and degree of translucency constancy more deeply by including in our analysis the variations in translucent appearance that are induced by the shape of the scattering phase function. This is an aspect of translucency that has been largely neglected. We used appearance matching to measure how perceived translucency depends on both lighting and phase function. The stimuli were rendered scenes that contained a figurine and the lighting direction was represented by spherical harmonic basis function. Observers adjusted the density of a figurine under one lighting condition to match the material property of a target figurine under another lighting condition. Across the trials, we varied both the lighting direction and the phase function of the target. The phase functions were sampled from a 2D space proposed by Gkioulekas et al. (2013) to span an important range of translucent appearance. We find the degree of translucency constancy depends strongly on the phase function's location in the same 2D space, suggesting that the space captures useful information about different types of translucency. We also find that the geometry of an object is important. We compare the case of a torus, which has a simple smooth shape, with that of the figurine, which has more complex geometric features. The complex shape shows a greater range of apparent translucencies and a higher degree of constancy failure. In summary, humans show significant failures of translucency constancy across changes in lighting direction, but the effect depends both on the shape complexity and the translucency phase function.

We previously showed that different types of aberration defocus, coma, and secondary astigmatism affect reading performance via different mechanisms. In this paper, we show the contrary result that, for identification of isolated letters, the effects of rendering different types of aberration can be described by a single cross-correlation-based metric. Aberrations reduce the effective resolution of an optical system, quantified by the high-frequency fall-offof the modulation transfer function. They additionally cause spatial-frequencydependent phase and contrast changes, which have a size-dependent effect on letter forms. We used contrast threshold as our performance measure, instead of distance acuity, to separate the effects of form alterations from those of resolution limits. This measure is additionally appropriate in comparing single-letterbased performance to reading at a fixed distance. The relationship between a cross-correlation-based measure of letter confusability and performance was the same for all three types of aberration. For reading, we had found a different relationship for coma than for defocus and secondary astigmatism. We conclude that even when two tasks-letter identification and reading-use the same component stimulus set, the combination of multiple letters in a reading task produces functional differences between the effects of these aberrations that are not present for isolated letters. © 2013 ARVO.

The allocation of visual attention is known to be influenced by objects (B. Scholl, 2001). This object sensitivity is commonly assumed to derive from a pre-attentive stage of scene segmentation that provides a parallel representation of important structural features that can play a functional role in guiding the allocation of processing resources. In many standard "objectbased attention" experiments, however, no more than two objects are ever presented. Moreover, these objects are typically presented at a predictable location for up to a second before the participant is cued to allocate attention to these objects (R. Egly, J. Driver, & R. D. Rafal, 1994). One can, therefore, ask whether many standard object-based attentional paradigms really support the notion of a parallel and pre-attentional representation. Our results, however, support the commonly held assumption that numerous objects can be maintained in parallel. Indeed, in apparent contrast to other object-based paradigms, where limits of up to (a "magic number") four are often observed, this paper found that at the least twelve objects could be maintained as potential units of selection. The results, therefore, provide evidence that the object segmentation involved in this object-based attention paradigm derives from a representation of numerous potential units of attentional selection that are maintained in parallel. © ARVO.

In this paper, we examine the mechanisms underlying the perceptual integration of two types of contour: snakes (composed of Gabor elements parallel to the path of the contour) and ladders (with elements perpendicular to the path). We varied the element separation and carrier wavelength. Increasing the element separation impaired detection of snakes but did not affect ladders; at high separations, snakes and ladders were closely matched in difficulty. One subject showed no effect of carrier wavelength, and the other showed a decline in performance as the wavelength increased. We discuss how these results might be accommodated by association field models. We also present a new model in which the linkage results from overlap in the filter responses to adjacent elements. We show that, if 1st-order filters are used, the model's performance on widely spaced snake contours deteriorates greatly as the carrier wavelength of the elements decreases, in contrast to our psychophysical results. To integrate widely spaced contours with short carrier wavelengths, the model requires a 2nd-order process, in which a nonlinearity intervenes between small-scale 1st-stage filters and large-scale 2nd-stage filters. This model detects snakes when the 1st and 2nd stage filters have the same orientation, and detects ladders when they are orthogonal.

We examined whether observers veridically perceive the reflectances of real objects under natural viewing conditions. A new forced-choice paradigm was used to measure observers' abilities to identify (not match) the reflectance of randomly crumpled gray papers across two levels of illumination, and also to simultaneously measure brightness discrimination thresholds for the same objects. Accuracy of lightness identification differed qualitatively among observers. By explicitly manipulating observer strategies, we show that when observers use brightness dissimilarity, their performance is similar to lightness identification. A brightness adaptation model simulates how instead of extracting lightness, observers can rely on perceived relative brightness to achieve the measured degrees of lightness identification.