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Call for Papers
Special Issue
CLASSIFICATION IMAGES: A TOOL TO ANALYZE VISUAL STRATEGIES
In 1970, Albert Ahumada and John Lovell applied multiple regression analysis
to the problem of auditory detection of a tone in noise to estimate the
contribution of auditory stimulus features to the observer's decision
variable. The regression weights plotted as a function of feature temporal
frequency could be called classification plots. The central concept of the
technique is the correlation over sets of stimuli of observer decisions with
noisy stimulus features. From the correlation of the features with the
decisions and the inter-correlations among the features, the investigator
can then estimate how the observer is weighting the stimulus features to
reach a decision.
In 1996, Ahumada and Beard applied the technique in the visual domain to
study vernier acuity tasks and revealed that human observers weighted the
visual information of the stimuli differently from the optimum (ideal)
observer. They used image pixel intensity as the stimulus features, so that
the stimulus feature weights did form an actual classification image.
Using a related technique (reverse correlation) Ringach, Hawken and Shapley
(1997) studied the orientation tuning in the macaque primary visual cortex.
They found that the orientation tuning and dynamics of the responses
differed for the input and output layers of V1.
In the last few years, investigators have applied the technique to study
many tasks and aspects of human vision including detection, blob and letter
discrimination, perceptual learning, illusory contours, attention,
performance of fovea vs. periphery, stereo, and off-frequency looking in
non-white noise.
For this special issue we welcome submission of papers that apply
classification image or related techniques to any aspect of biological
vision, including papers that focus on theoretical or methodological aspects
of the technique.
The Journal of Vision is published on the internet by the Association for
Research in Vision and Ophthalmology. Papers published in the journal are
freely and permanently accessible to all vision scientists throughout the
world. Contributors to the Journal of Vision are encouraged to use images,
color, movies, and other digital enhancements to help communicate their
ideas.
Guest Editors:
Miguel P. Eckstein
Department of Psychology
University of California, Santa Barbara
eckstein@psych.ucsb.edu
Albert Ahumada Jr.
NASA Ames Research Center
al@vision.arc.nasa.gov
Deadline for submissions: June 1, 2001
Target publication date: September 1, 2001
Authors interested in submitting a paper to this special issue should follow
the Instructions for Authors at <http://journalofvision.org/>
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