The psychophysics of visual search.

By John Palmer, Preeti Verghese, M. Pavel. 2000

471 citations recorded by the source corpus.

Subfields: Cognitive Neuroscience, Experimental and Cognitive Psychology

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In Cognitive Neuroscience

In Experimental and Cognitive Psychology

Citations in the corpus

Visual search and selective attention (2006, background): “With increasing display size, the number of sources of noise (ie, uncertainty) increases and performance declines (Palmer, Verghese, & Pavel, 2000 ).”
Visual attention: The past 25 years (2011, background): “(c and d) Small s attention is shown in b and d. Shown are plots of psychometric functions for each contrast yielding half-maximum performance; d0max, asymptotic performance at high nts are ±i.e. Error bars on parameter estimates are confidence intervals obtained by (Herrmann et al., 2010).”
Serial deployment of attention during visual search. (2003, background): “This is called the decision-noise explanation of nonzero search slopes (for extensive discussions, see Palmer, Verghese, & Pavel, 2000; Sperling & Dosher, 1986).”
Attentional modulation of visual processing. (2004, background): “…appearing against a blank background, a more ecologically relevant purpose is served by attentional selection, the selection of behaviorally relevant stimuli from among competing distracters (Duncan & Humphreys 1989, Palmer et al. 2000, Treisman & Gelade 1980, Verghese 2001, Wolfe et al. 1989).”
Crowding is unlike ordinary masking: distinguishing feature integration from detection. (2004, background): “” Whether to call this a dichotomy has become controversial, as there is a continuum of intermediate cases (Bergen & Julesz, 1983; Nakayama & Silverman, 1986; Duncan & Humphreys, 1989; Verghese & Pelli, 1992; Wolfe, Friedman-Hill, Stewart, & O'Connell, 1992; Verghese & Nakayama, 1994; Wolfe, 1998; P”
Optimal eye movement strategies in visual search (2005, background): “∑ ( 1 ) where n is the number of potential target locations, i W is the template response from the i th”
Visual Clutter Causes High-Magnitude Errors (2006, background): “Nor is it consistent with high-threshold theories of visual search that assume that errors are due to noisiness at the decision stage (see [ 7 ] for review).”
A detection theory account of change detection. (2004, methodology): “In cases in which change involves a single target element, the MAD model approximates the performance of an ideal observer (Palmer et al., 2000).”
What attributes guide the deployment of visual attention and how do they do it? (2004, background): “More formal signal detection approaches (generally involving relatively simple stimuli) can be found elsewher”
Visual Search and Attention: Review A Signal Detection Theory Approach (2001, unknown): “Palmer et al. (2000) have shown that accuracy in finding the target decreases as a function of sigmasite orientation as compared to surrounds with the same orientation, averaged across all the cells in the sample, ratio, which is the ratio of the standard deviations of the distractor to the target…”
The New C Standard (Excerpted material) An Economic and Cultural Commentary (2008, unknown): “While there have been a considerable number of studies[254] investigating visual search, most have involved searching for objects of different shapes and colors rather than words.”
Compulsory averaging of crowded orientation signals in human vision (2001, background): “and commonly observed in visual search tasks in which the presence of distractors can impair performance without interacting with the targe”