The effect of contrast and size scaling on face perception in foveal and extrafoveal vision.

PURPOSE: To determine whether face perception can be equalized across the visual field by scaling size and contrast simultaneously. METHODS: Contrast sensitivities were measured for detection (N = 1) and identification (N = 2-8) of a target face as a function of size (0.4 degrees-10 degrees) across eccentricities (E = 0 degrees-10 degrees). RESULTS: In all conditions contrast sensitivity first increased and then saturated, as a function of stimulus size. Maximum sensitivity (Smax) decreased, whereas critical size (where S = Smax/square root(2)) increased with eccentricity and set size (N). At each set size, sensitivities from all eccentricities could be equated by double scaling--i.e., translation in horizontal (size) and vertical (contrast) dimensions on log-log axes. Similarly, at each eccentricity, data from all set sizes could be superimposed using double scaling. Furthermore, all data could be superimposed onto the foveal detection curve when double scaled according to the equation F = 1 + E/E2i + logN/logN2i + E(logN)/K, where i is horizontal or vertical. This equation incorporates the eccentricity (E2) and set size (N2), where contrast and size double, as well as the interaction term (K). CONCLUSIONS: Double scaling superimposes data. Not only is this possible across set sizes or eccentricities separately, but by combining their effects, a function is provided that collapses all data to a single curve, explaining all performance variation across eccentricity and set size. Our results support the proposition based on numeral recognition that failures of spatial scaling across eccentricities may simply reflect the need for scaling both size and contrast.

Scaling extrafoveal detection of distortion in a face and grating.

Peripheral performance involving simple visual tasks and stimuli can be equated with foveal performance by spatial scaling, whilst more complex tasks and stimuli seem to need additional scaling of image contrast. We therefore determined whether the contrast manipulation needed to compensate for eccentricity-dependent performance changes is due to an increase in stimulus or task difficulty. We measured contrast sensitivities to determine foveal and peripheral ability to discriminate between an original and a distorted version of a polar-circular sinusoidal grating and a face image. Contrast sensitivities as a function of image size were spatially scaleable across eccentricities for both the face and grating. Furthermore, irrespective of stimulus, performance could be scaled with the same individual E2 value. Thus task simplicity overrides the nature of the stimulus in determining scaling requirements, suggesting that it is the complexity of the task, not of the stimulus, that makes contrast scaling necessary in complex tasks.

Modeling spatial integration and contrast invariance in visual pattern discrimination.

PURPOSE: Human pattern discrimination performance has been reported to be largely independent of stimulus contrast but to depend on stimulus area. The authors propose a model that combines the effects of spatial integration and contrast. The model is based on the computation of similarity between pattern templates in memory and signals to be discriminated using normalized correlation. There are also two sources of additive noise, one before and one after the computation of correlation. The model was compared with human observers in an orientation discrimination task. METHODS: Orientation discrimination thresholds of human observers were measured for sinusoidal gratings of various areas, contrasts, and spatial frequencies. A two-interval, forced-choice methods was used. The performance of the model was determined by using computer simulations. RESULTS: It was found that the effects of contrast and grating area were interrelated. The decrease of orientation thresholds as a function of grating area was considerably larger at low than at high contrast. On the other hand, orientation thresholds decreased clearly as a function of contrast at the smallest grating areas but hardly at all at the largest grating areas. The model accounted well for the experimental findings. CONCLUSIONS: Because the invariance of orientation discrimination with respect to stimulus contrast depended on area, the cause of the invariance appeared to occur after spatial integration. The model explains this so that, with increasing contrast or area, the normalized correlation gradually approached a constant value. The proportion of pretemplate noise became negligible compared to the constant posttemplate noise. Thus, total noise also approached a constant value. Hence, the signal-to-noise ratio and discrimination performance became constant.

Qualitative cues in the discrimination of affine-transformed minimal patterns.

An important factor in judging whether two retinal images arise from the same object viewed from different positions may be the presence of certain properties or cues that are 'qualitative invariants' with respect to the natural transformations, particularly affine transformations, associated with changes in viewpoint. To test whether observers use certain affine qualitative cues such as concavity, convexity, collinearity, and parallelism of the image elements, a 'same-different' discrimination experiment was carried out with planar patterns that were defined by four points either connected by straight line segments (line patterns) or marked by dots (dot patterns). The first three points of each pattern were generated randomly; the fourth point fell on their diagonal bisector. According to the position of that point, the patterns were concave, triangular (three points being collinear), convex, or parallel sided. In a 'same' trial, an affine transformation was applied to one of two identical patterns; in a 'different' trial, the affine transformation was applied after the point lying on the diagonal bisector was perturbed a short, fixed distance along the bisector, inwards for one pattern and outwards for the other. Observers' ability to discriminate 'same' from 'different' pairs of patterns depended strongly on the position of the fourth, displaced, point: performance varied rapidly when the position of the displaced point was such that the patterns were nearly triangular or nearly parallel sided, consistent with observers using the hypothesised qualitative cues. The experimental data were fitted with a simple probabilistic model of discrimination performance that used a combination of these qualitative cues and a single quantitative cue.

A window model for spatial integration in human pattern discrimination.

PURPOSE: A simple model of human visual pattern discrimination was designed and tested experimentally. The model is based on two assumptions. First, at any glimpse the spatial integration of image information is limited to a window. Second, the observer generates a tailored discriminator for the signals in question using available information. The model is composed of a spatial integration window followed by an ideal discriminator. METHODS: The model was tested by comparing its performance with that of human observers in orientation and contrast discrimination. Using a two-alternative, forced-choice method, human orientation and contrast discrimination thresholds were measured for cosine gratings of various areas and spatial frequencies in the presence of two-dimensional spatial noise. RESULTS: Orientation discrimination thresholds decreased considerably with increasing grating area. Thus, there was clear spatial integration. However, in contrast discrimination, thresholds appeared to decrease only slightly. To make the two tasks comparable, the results also were expressed in terms of efficiency. Human efficiency decreased with grating area in a similar way in the two tasks. This suggests that the factors limiting spatial integration are the same in both tasks. Indeed, the threshold data were explained by the model with the same window size in both tasks with good accuracy. The absolute performance of the model was approximately equal to that of human observers. CONCLUSIONS: The success of the model supports the hypothesis of a spatial integration window. It also supports the idea that human observers use knowledge about the signals to generate an efficient discriminator.