Faculty Opinions recommendation of A note on detecting statistical outliers in psychophysical data.

2020 ◽  
Author(s):  
David H Foster
Keyword(s):  
Psychophysical Data

Comparison of visual (MUNSELL) and instrumental measures (CIELAB) of coloured textile standard samples

2019 ◽  
Vol 23 (4) ◽  
pp. 340-354
Author(s):  
Asim Kumar Roy Choudhury ◽  
Biswajit Naskar
Keyword(s):  
Correlation Coefficient ◽  
Design Methodology ◽  
Correlation Coefficients ◽  
Standard Samples ◽  
Content Type ◽  
Psychophysical Data ◽  
Physical Data ◽  
Hue Angle ◽  
Munsell Scale

Purpose This paper aims to compare visual (Munsell) and instrumental (CIELAB) attributes of SCOTDIC colour standards. Design/methodology/approach SCOTDIC cotton and polyester standards of defined hue, value and chroma were subjected to spectrophotometric assessment for finding the corresponding instrumental parameters. The visual and instrumental parameters were compared. Findings The correlation between SCOTDIC value and CIELAB lightness is quite high. Correlation coefficient between SCOTDIC hue and CIELAB hue angle and the correlation between SCOTDIC chroma and CIELAB chroma were only moderate because the CIELAB chroma varied widely at higher chroma. When the standards of SCOTDIC hues having erratic hue angles at two extremes are excluded, the Correlation coefficients between SCOTDIC hue and CIELAB hue angle become high. Research limitations/implications The psychophysical data (visual) are difficult to match with physical data (instrumental). Originality/value The object of the present research is to study and compare visual (Munsell) and instrumental (CIELAB) colorimetric parameters. Munsell scale is physically exemplified by SCOTDIC fabric samples available in two sets, namely, cotton and polyester sets.

There is No Evidence That Kanizsa-Type Subjective Contours Can Be Detected in Parallel

Perception ◽  
1996 ◽  
Vol 25 (7) ◽  
pp. 861-874 ◽  
Author(s):  
Rick Gurnsey ◽  
Frédéric J A M Poirier ◽  
Eric Gascon
Keyword(s):  
Visual Search ◽  
Control Problem ◽  
Search Task ◽  
Visual Search Task ◽  
Physiological Data ◽  
Sufficient Information ◽  
Parallel Search ◽  
High Contrast ◽  
Psychophysical Data ◽  
Area V2

Davis and Driver presented evidence suggesting that Kanizsa-type subjective contours could be detected in a visual search task in a time that is independent of the number of nonsubjective contour distractors. A linking connection was made between these psychophysical data and the physiological data of Peterhans and von der Heydt which showed that cells in primate area V2 respond to subjective contours in the same way that they respond to luminance-defined contours. Here in three experiments it is shown that there was sufficient information in the displays used by Davis and Driver to support parallel search independently of whether subjective contours were present or not. When confounding properties of the stimuli were eliminated search became slow whether or not subjective contours were present in the display. One of the slowest search conditions involved stimuli that were virtually identical to those used in the physiological studies of Peterhans and von der Heydt to which Davis and Driver wish to link their data. It is concluded that while subjective contours may be represented in the responses of very early visual mechanisms (eg in V2) access to these representations is impaired by high-contrast contours used to induce the subjective contours and nonsubjective figure distractors. This persistent control problem continues to confound attempts to show that Kanizsa-type subjective contours can be detected in parallel.

A Digital Test Chart for Visual Assessment of Color Appearance Scales

2021 ◽  
Vol 2021 (29) ◽  
pp. 160-165
Author(s):  
Mark D. Fairchild
Keyword(s):  
Human Perception ◽  
Visual Assessment ◽  
Model Testing ◽  
Color Appearance ◽  
Psychophysical Data ◽  
Appearance Models ◽  
Digital Test ◽  
Computational Comparison

A digital color appearance test chart, akin to a ColorChecker® Chart for human perception, was developed and evaluated both perceptually and computationally. The chart allows an observer to adjust the appearance of a limited number of color patches to allow a quick evaluation of perceived brightness, colorfulness, lightness, saturation, and hue on a display. The resulting data can then be used to compared observed results with the predictions of various color appearance models. Analyses in this paper highlight some known shortcomings of CIELAB, CIECAM02, and CAM16. Differences between CIECAM02 and CAM16 are also highlighted. This paper does not provide new psychophysical data for model testing, it simply describes a technique to generate such data and a computational comparison of models.

Movements of the Mental Eye in Pictorial Space

2005 ◽  
Author(s):  
Jan J. Koenderink
Keyword(s):  
Physical Space ◽  
Physical Object ◽  
Current Understanding ◽  
Pictorial Space ◽  
Psychophysical Data ◽  
Pictorial Perception ◽  
Mental Object

When an observer is faced with a straight photograph, the observer can either look at the image or look into the photograph. This manner of observing photographs presents a difference that is crucial. In the former case, the observer is aware of the photograph as a physical object in a physical space while in the latter, the observer is aware of the pictorial object in a pictorial space. This chapter focuses on the current understanding of pictorial perception and the structure of pictorial space. Pictorial space is different from physical space in that it does not exist outside of the observer's awareness. It is a thread of consciousness and a purely mental object. In contrast, the photograph as a physical object is a mere planar sheet composed of pigments in a certain simultaneous order. The concepts of pictorial object and scene is not limited to the earlier existence of a physical space that figured casually in the present existence of the photograph. The theory of pictorial space is largely derived from psychophysical data. The measurement of it depends on the idiosyncratic movements of the mental eye. It is purely an ‘intentional entity’ that makes its elusive to physiological methods and susceptible to misconception.

Psychophysical Methodology: Comparisons within the Method of Limits

1969 ◽  
Vol 28 (2) ◽  
pp. 503-514 ◽  
Author(s):  
Robert M. Herrick
Keyword(s):  
Stimulus Intensity ◽  
Present Method ◽  
Psychophysical Experiment ◽  
Psychophysical Data ◽  
Threshold Distribution ◽  
The Mean

Assume that, in a “Yes”—“No” psychophysical experiment, the probability of a “Yes” response increases as the stimulus intensity increases. Then, on the basis of probability considerations (a) the mean threshold of the descending method of limits (DML) is greater than the mean threshold of the ascending method of limits (AML) and (b) σ of the DML threshold distribution may be greater than, equal to, or less than σ of the AML threshold distribution. The implications of these and other deductions are considered with respect to analyses of psychophysical data. For example, one deduction indicates that the present method for evaluating errors of habituation and expectation is wrong. Data that support the deductions are included.

Neurophysiological Contributions to Luminance and Chromatic Mechanisms in a Hyperacuity Task

Perception ◽  
1997 ◽  
Vol 26 (1_suppl) ◽  
pp. 339-339
Author(s):  
L Rüttiger ◽  
B B Lee
Keyword(s):  
Detection Threshold ◽  
Luminance Contrast ◽  
Contrast Threshold ◽  
Psychophysical Data ◽  
Spatial Mechanisms ◽  
Cone Cells

We recently reported (paper presented at ARVO 1997) psychophysical evidence as to contributions of luminance and chromatic mechanism in a hyperacuity task, namely detection of small displacements. Achromatic or chromatic (430, 550, 690 nm) edges were presented on white or chromatic (550 nm) backgrounds, and displacement thresholds measured as a function of luminance contrast. Above 3% (achromatic detection threshold), all conditions yielded nearly identical contrast/threshold curves; we believe a luminance mechanism to be responsible. In chromatic conditions, below 3% contrast, large (>100 s arc) displacements were detectable; presumably chromatic mechanisms are responsible. We have now carried out equivalent physiological experiments. Data were consistent with cells of the magnocellular (MC) pathway underlying the luminance mechanism. Opponent S-cone or parvocellular (PC) cells became responsive to displacements in the chromatic conditions. S-cone cells were very responsive to the 430 nm edge, and responded at low contrasts matching the psychophysical thresholds. L, M-cone opponent cells were responsive to the 690 nm edge, but less so than was expected from the psychophysical data. Our data suggest MC-cells underlie a luminance hyperacuity mechanism. Additional factors (eg cell numerosity) may have to be considered for chromatic spatial mechanisms.

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