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Because of the great heterogeneity of subjects and styles, esthetic perception delineates a special and elusive field of research in vision, which represents an interesting challenge for cognitive science tools. With specific regard to the role of visual complexity, in this paper we present an experiment aimed to measure this dimension in a heterogeneous set of paintings. We compared perceived time complexity measures - based on a temporal estimation paradigm - with physical and statistical properties of the paintings, obtaining a strong correlation between psychological and computational results.

This paper calls attention to research showing that binocular disparity, which is an effective cue to depth, plays a secondary role, at best, in the perception of 3D shape. This claim has implications both for how shape should be studied and how this unique perceptual property should be modeled. These issues are discussed from a historical perspective, which shows how the failure to appreciate the importance of the Gestalt grouping principle called 'Figure-Ground Organization' led to many unfruitful efforts. It also calls attention to how this situation can be remedied.

When presented against a highly lit black background, dimly illuminated white paper strips appear white even when they are equiluminant with the background. Such an example of simultaneous lightness constancy cannot be accounted for by receptor gain control because of the equiluminance. Moreover, this demonstration shows that lightness cannot be reduced to 'relative brightness' as is widely believed.

I consider how structure is derived from texture containing changes in orientation over space, and propose that multi-local orientation variance (the average orientation variance across a series of discrete images locales) is an estimate of the degree of organization that is useful both for spatial scale selection and for discriminating structure from noise. The oriented textures used in this paper are Glass patterns, which contain structure at a narrow range of scales. The effect of adding noise to Glass patterns, on a structure versus noise task (Maloney et al., 1987), is compared to discrimination based on orientation variance and template matching (i.e. having prior knowledge of the target's orientation structure). At all but very low densities, the variance model accounts well for human data. Next, both models' estimates of tolerable orientation variance are shown to be broadly consistent with human discrimination of texture from noise. However, neither model can account for subjects' lower tolerance to noise for translational patterns than other (e.g. rotational) patterns. Finally, to investigate how well these structural measures preserve local orientation discontinuities, I show that the presence of a patch of unstructured dots embedded in a Glass pattern produces a change in multi-local orientation variance that is sufficient to account for human detection (Hel Or and Zucker, 1989). Together, these data suggest that simple orientation statistics could drive a range of 'texture tasks', although the dependency of noise resistance on the pattern type (rotation, translation, etc.) remains to be accounted for.

In this paper some issues are considered related to the encoding of spatial information and associated perceptual learning algorithms which, it is claimed, are necessary for robust pattern and object recognition in multi-object (natural) scenes. The types of learning requirements within a 'recognition-by-parts' paradigm are contrasted with findings from alternative models.

Many researchers have proposed that objects are perceived as structural descriptions, which specify the configuration of an object's features (or parts) in terms of their categorical relations to one another. Others have proposed that objects are perceived as views, which specify the configuration of an object's features in terms of their coordinates, in particular 2D views. This paper presents five experiments testing these competing accounts of the perception of the configuration of an object's features. Subjects learned to recognize a set of target objects and were tested for their ability to distinguish them from various distractors that differed either in their categorical relations or their coordinates. Subjects were consistently more likely to confuse both 2D and 3D objects that were similar in their parts' relations to each other than to confuse objects similar in their parts' coordinates (in any reference frame). This effect persisted when subjects were allowed to view the objects as long as they wished and when they were explicitly trained to distinguish them from the distractors. These findings suggest that we perceive an object's features in terms of their categorical relations to one another. A preliminary model of the findings is presented.

In this paper, a model is proposed for bilateral symmetry detection in images consisting of dense arrangements of local features. The model is elaborated on the basis of a psychophysical experiment showing that grouping precedes and facilitates symmetry detection. The proposed computational model consists of three stages: a grouping stage, a symmetry-detection stage, and a symmetry-subsumption stage. Reliance upon a preliminary grouping stage enables a significant reduction of the computational load for detecting symmetry. An implementation of the model is described, and results are presented, showing a good agreement of the model performance with human symmetry perception.

This paper reviews empirical evidence for the detection of visual symmetries and explanatory theories and models of symmetry detection. First, mirror symmetry is compared to other types of symmetry. The idea that symmetry detection is preattentive is then discussed and other roles that attention might play in symmetry detection are considered. The major part of the article consists of a critical examination of the extensive literature about the effects on symmetry detection of several major factors such as the orientation of the symmetry axis, the location of the stimulus in the visual field, grouping, and perturbations. Constraints on plausible models of symmetry detection are derived from this rich database and several proposals are evaluated against it. As a result of bringing this research together, open questions and remaining gaps to be filled by future research are identified.

Textural segmentation plays an important role in the figure-ground discrimination process. Evidence from neuroscience and psychophysics suggests that the segregation of texture patterns composed of oriented line segments is strongly influenced by the orientation contrast between the patterns (Nothdurft, Vision Res. 31, 1073-1078, 1991). In contrast to models available in the literature, this paper presents a neural network architecture for textural segmentation that can adaptively delimit the boundaries of uniformly textured regions. Cells with adaptive receptive fields encode uniformly textured regions by diffusively interpolating the estimates of feature orientations across the image. Orientation contrast boundaries are detected at gradients across the interpolated regions to produce the final segmentation. Consistent with neurophysiological data from simple and complex cells sensitive to static and moving textural patterns (Hammond and MacKay, Exp. Brain Res. 30, 275-296, 1977), the present model suggests that preattentive textural segregation can be performed by early visual processes localized to areas V1, V2, and perhaps V3 or V5. The computational results further support the idea that textural segmentation should not be thought of as a 'static' process, but as a system that employs cells with context-dependent response characteristics (Gilbert and Wiesel, Vision Res. 30, 1689-1701, 1990), here modeled as adaptive receptive fields.

Some symmetries (e.g. bilateral, rotational, translational) only describe quite specialized shapes, but differential symmetry axes (e.g. Blum, J. Theoret. Biol. 38, 205-287, 1973; Brady and Asada, Int. J. Robotics Res. 3, 36-61, 1984) describe more general shapes. Such axes are of interest in part because they form the 'backbone' of generalized cylinder and other shape representations used in shape recognition (e.g. Marr, Vision, W. H. Freeman and Co., NY, 1982; Biederman, Psychol. Rev. 94, 115-147, 1987). However, despite the popularity of these representations as psychological models, algorithms from machine vision for computing them have strong limitations as psychological models. This paper presents two versions of a network model, one of which is more plausible as a psychological model because it derives symmetry axes from the activations of idealized visual receptive fields.

In this paper an attempt is made to review the types of processes developed by the author, and others, to classify and segment textures and to compare, where possible, such algorithms with what has been proposed to occur in human vision. In particular, this paper is concerned with evaluating the proposed constituent processes from a 'cognitive engineering' perspective where, in order to have an adequate model for either human or machine texture processing, complete segmentation or classification or both must be attained.

For the purpose of quantifying models of letter recognition, similarities are often specified in terms of stimulus properties. In this paper, an approach is advocated based on similarities between internal letter representations or internal letter images, i.e. it is argued that optical and retinal factors play a more prominent role in letter confusions than is usually assumed. To illustrate this, letter images were calculated on the basis of earlier experimentally determined point spread functions (Blommaert et al., Spatial Vision 2, 99-115, 1987). Next, data on confusion matrices from Bouma (Vision Res. 11, 459-474, 1971) were taken to evaluate different measures which might be useful for quantifying similarities between internal letter representations. In the analysis of experimental data, Luce's (In: Handbook of Mathematical Psychology, 1963) choice model was used. It was found that if similarities were expressed in terms of differences between image contours, a fair first order approximation of Bouma's experimental results could be formulated (overall correlation coefficient of 0.95). Other measures like correlations between spatial frequency spectra of letter images were found to be less successful. The method used provides a means to relate quantitatively stimulus features and optical and early-visual factors to letter confusions.

The present paper proposes a mathematical theory and a method of recognition of both the 3D structure and the motion of a moving object from its monocular image. Initially, characteristic features are extracted from the 2D perspective image of the object. Because motion of the object induces a change in its 2D perspective image, it also induces a change in the features which depends on the 3D structure and the velocity of the object. This suggests the possibility of detecting the 3D structure and the motion directly from the features and their changing rate, without the need for calculating optical flows. An analysis is made of the relation between the 3D rigid motion of a surface element and the change in local linear features. From this relation, a method is proposed for calculating the velocity of and the normal to the surface element without considering any correspondence of points. An optical flow can also be calculated by this method. Two simple computer simulations are provided.

A typical characteristic of columns in Doric temples is entasis; a slight convexity in the body of a column. Often, and particularly in guide-books, it is suggested that entasis is intended to compensate for an illusion of concavity in columns with truly straight sides. We have investigated whether any such visual illusion exists, both in parallel sided and in tapering columns in a series of experiments, finding little evidence to support any illusion-compensation theory. Further, we explored the possibility that entasis was employed for purely aesthetic reasons, but the results do not support this conclusion. Finally, evidence supporting an engineering role for entasis is presented. [ABSTRACT FROM AUTHOR]

The article discusses the use of scientific perspective in analyzing visual arts. Visual science transcends the totality of individual components of visual arts to uncover perceptual meaning. Lines and colors serve as means to convey perceived meaning and artistic value embodying physiognomic perceptual properties, feelings and thoughts.

Early 20th century artists including Duchamp and Balla tried to portray moving objects on a static canvas by superimposing objects in successive portrayals of an action. We investigated whether implied motion in those paintings is associated with activation of motion-sensitive area MT+. In Experiment 1, we found that observers rated these kinds of paintings higher in portraying motion than they did other abstract paintings in which motion is not intended. We also found that observers who had previously experienced abstract paintings with implied motion tended to give higher motion ratings to that class of paintings. In Experiment 2, we used functional magnetic resonance imaging (fMRI) to measure brain activity of observers while viewing abstract paintings receiving the highest and the lowest motion rating scores in Experiment 1. We found MT+, but not primary visual cortex (V1), showed greater BOLD responses to abstract paintings with implied motion than to abstract paintings with little motion impression, but only in observers with prior experience viewing those kinds of paintings. These results imply that the neural machinery ordinarily engaged during perception of real visual motion is activated when people view paintings explicitly designed to convey a sense of visual motion. Experience, however, is necessary to achieve this sense of motion. [ABSTRACT FROM AUTHOR]

How do visual form and motion processes cooperate to compute object motion when each process separately is insufficient? Consider, for example, a deer moving behind a bush. Here the partially occluded fragments of motion signals available to an observer must be coherently grouped into the motion of a single object. A 3D FORMOTION model comprises five important functional interactions involving the brain's form and motion systems that address such situations. Because the model's stages are analogous to areas of the primate visual system, we refer to the stages by corresponding anatomical names. In one of these functional interactions, 3D boundary representations, in which figures are separated from their backgrounds, are formed in cortical area V2. These depth-selective V2 boundaries select motion signals at the appropriate depths in MT via V2-to-MT signals. In another, motion signals in MT disambiguate locally incomplete or ambiguous boundary signals in V2 via MT-to-V1-to-V2 feedback. The third functional property concerns resolution of the aperture problem along straight moving contours by propagating the influence of unambiguous motion signals generated at contour terminators or corners. Here, sparse 'feature tracking signals' from, for example, line ends are amplified to overwhelm numerically superior ambiguous motion signals along line segment interiors. In the fourth, a spatially anisotropic motion grouping process takes place across perceptual space via MT-MST feedback to integrate veridical feature-tracking and ambiguous motion signals to determine a global object motion percept. The fifth property uses the MT-MST feedback loop to convey an attentional priming signal from higher brain areas back to V1 and V2. The model's use of mechanisms such as divisive normalization, endstopping, cross-orientation inhibition, and long-range cooperation is described. Simulated data include: the degree of motion coherence of rotating shapes observed through apertures, the coherent vs. element motion percepts separated in depth during the chopsticks illusion, and the rigid vs. nonrigid appearance of rotating ellipses. [ABSTRACT FROM AUTHOR]

The 'colour-shading effect' describes the phenomenon whereby a chromatic pattern influences perceived shape-from-shading in a luminance pattern. Specifically, the depth corrugations perceived in sinusoidal luminance gratings can be enhanced by spatially non-aligned, and suppressed by spatially aligned sinusoidal chromatic gratings. Here we examine whether colour contrast can influence perceived shape in patterns that combine shape-from-shading with shape-from-texture. Stimuli consisted of sinusoidal modulations of texture (defined by orientation), luminance and colour. When the texture and luminance modulations were suitably combined, one obtained a vivid impression of a corrugated depth surface. The addition of a colour grating to the texture-luminance combination was found to enhance the impression of depth when out-of-phase with the luminance modulation, and suppress the impression of depth when in-phase with the luminance modulation. The degree of depth enhancement and depth suppression was approximately constant across texture amplitude when measured linearly. In the absence of the luminance grating however, the colour grating had no phase-dependent affect on perceived depth. These results show that colour contrast modulates the contribution of shading to perceived shape in combined shading and texture patterns. [ABSTRACT FROM AUTHOR]

Dynamic texture spreading is a filling-in phenomenon where a colored pattern perceptually spreads onto an area confined by virtual contours in a multi-aperture motion display. The spreading effect is qualitatively similar to static texture spreading but widely surpasses it in strength, making it particularly suited for quantitative studies of visual interpolation processes. We first carried out two experiments to establish with objective tasks that texture spreading is a genuine representation of surface qualities and thus goes beyond mere contour interpolation. Two subsequent experiments serve to relate the phenomenon to ongoing discussions about potentially responsible mechanisms for spatiotemporal integration. With a phenomenological method, we examined to what extent simple sensory persistence might be causally involved in the effect under consideration. Most of our findings are consistent with the idea of sensory persistence, and indicate that information fragments are integrated over a time window of about 100 to 180 ms to form a complete surface representation. [ABSTRACT FROM AUTHOR]

Marvin M. Chun and Yuhong Jiang (1998) investigated the role of spatial context on visual search. They used two display conditions. In the Old Display condition, the spatial arrangement of items in the search display was kept constant throughout the experiment. In the New Display condition, the spatial arrangement of items was always novel from trial to trial. The results showed better performance with Old Displays than with New Displays. The authors proposed that repeated spatial context help guiding attention to the target location, thus they termed this effect Contextual Cueing. We present three attempts to reproduce this effect. Experiments 1 and 2 were near exact replications of experiments in Chun and Jiang's report, where we failed to obtain Contextual Cueing. Post-experimental interviews revealed that participants used different search strategies when performing the task: an 'active' strategy (an active effort to find the target), or a 'passive' strategy (intuitive search). In Experiment 3, we manipulated task instructions to bias participants into using active or passive strategies. A robust Contextual Cueing Effect was obtained only in the passive instruction condition. [ABSTRACT FROM AUTHOR]

Effects of viewpoint that are typically found in shape recognition tasks have been interpreted in the past as strong evidence against approaches based on the use of geometric invariants by the human visual system. At first sight, the use of such invariants would indeed predict shape recognition to be viewpoint independent. It has been argued before, however, that the visual estimation of invariants need not itself be invariant. Changes of viewpoint introduce changes in 2D stimulus features. The latter may make the estimation of invariants by the visual system more or less difficult. The present study explores how such 2D features influence estimation distributions in a reconstruction paradigm. Subjects were shown four coplanar dots. They were asked to estimate the position of one of the dots relative to the three others on the basis of a slanted version of the configuration. An estimation distribution was obtained for every position of the dot to be estimated. Biases in these distributions indicated that subjects performed the task by using 2D reference axes that were unambiguously identifiable in both the images of the dot pattern. [ABSTRACT FROM AUTHOR]

The ability to deal with object structure - to determine what is where in a given object, rather than merely to categorize or identify it - has been hitherto considered the prerogative of 'structural description' approaches, which represent shapes as categorical compositions of generic parts taken from a small alphabet. In this note, we propose a simple extension to a theoretically motivated and extensively tested appearance-based model of recognition and categorization, which should make it capable of representing object structure. We describe a pilot implementation of the extended model, survey independent evidence supporting its modus operandi, and outline a research program focused on achieving a range of object processing capabilities, including reasoning about structure, within a unified appearance-based framework. [ABSTRACT FROM AUTHOR]