Serial visual search from a parallel model q (original) (raw)
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2012
Humans perform visual search fairly efficiently, finding targets within only a few fixations. Data from eye-tracked participants was subjected to a fixation by fixation analysis to pinpoint why participants tended to make fewer fixations than would be expected by chance. The goal of this paper is to present a computational model that performs visual search as efficiently as humans. The model varied several components that may have aided visual search: memory, search strategy, and degree of parafoveal vision. Two dependent measures were used to evaluate the model: number of fixations to find the target and the distribution of saccade amplitudes. The best fitting model suggested that the biggest contribution to efficient search came from larger parafoveal vision. Search strategy, however, accounted for the distribution of saccade amplitudes.
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Modeling Efficient Serial Visual Search
Cognitive Science, 2012
Modeling Efficient Serial Visual Search Bella Z. Veksler (bellav717@gmail.com) Air Force Research Laboratory, Wright-Patterson Air Force Base Dayton, OH 45431 USA Wayne D. Gray (grayw@rpi.edu) Cognitive Science Department, Rensselaer Polytechnic Institute Troy, NY 12180 USA Abstract Humans perform visual search fairly efficiently, finding targets within only a few fixations. Data from eye-tracked participants was subjected to a fixation by fixation analysis to pinpoint why participants tended to make fewer fixations than would be ex- pected by chance. The goal of this paper is to present a com- putational model that performs visual search as efficiently as humans. The model varied several components that may have aided visual search: memory, search strategy, and degree of parafoveal vision. Two dependent measures were used to eval- uate the model: number of fixations to find the target and the distribution of saccade amplitudes. The best fitting model sug- gested that the biggest co...
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The psychophysics of visual search
2000
Most theories of visual search emphasize issues of limited versus unlimited capacity and serial versus parallel processing. In the present article, we suggest a broader framework based on two principles, one empirical and one theoretical. The empirical principle is to focus on conditions at the intersection of visual search and the simple detection and discrimination paradigms of spatial vision. Such simple search conditions avoid artifacts and phenomena specific to more complex stimuli and tasks.
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