Human performance modeling: Difference between revisions

Revision as of 06:10, 28 September 2019

Revision as of 20:26, 29 September 2019

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===== [[Visual search|Visual Search]] =====

A developed area in attention is the control of visual attention - models that attempt to answer, "where will an individual look next?" A subset of this concerns the question of visual search: How rapidly can a specified object in the visual field be located? This is a common subject of concern for human factors in a variety of domains, with a substantial history in cognitive psychology. This research continues with modern conceptions of [[Salience (neuroscience)|salience]] and [http://www.scholarpedia.org/article/Saliency_map salience maps]. Human performance modeling techniques in this area include the work of Melloy, Das, Gramopadhye, and Duchowski (2006) regarding [[Markov models]] designed to provide upper and lower bound estimates on the time taken by a human operator to scan a homogeneous display.<ref>{{cite journal | last1 = Melloy | first1 = B. J. | last2 = Das | first2 = S. | last3 = Gramopadhye | first3 = A. K. | last4 = Duchowski | first4 = A. T. | year = 2006 | title = A model of extended, semisystematic visual search | url =http://andrewd.ces.clemson.edu/research/vislab/docs/MDGD-HF-2006.pdf | journal = Human Factors: The Journal of the Human Factors and Ergonomics Society | volume = 48 | issue = 3| pages = 540–554 | doi=10.1518/001872006778606840| pmid = 17063968 }}</ref> Another example from Witus and Ellis (2003) includes a computational model regarding the detection of ground vehicles in complex images.<ref>{{cite journal | last1 = Witus | first1 = G. | last2 = Ellis | first2 = R. D. | year = 2003 | title = Computational modeling of foveal target detection | url = | journal = Human Factors: The Journal of the Human Factors and Ergonomics Society | volume = 45 | issue = 1| pages = 47–60 | doi=10.1518/hfes.45.1.47.27231| pmid = 12916581 }}</ref> Facing the nonuniform probability that a menu option is selected by a computer user when certain subsets of the items are highlighted, Fisher, Coury, Tengs, and Duffy (1989) derived an equation for the optimal number of highlighted items for a given number of total items of a given probability distribution.<ref>{{cite journal | last1 = Fisher | first1 = D. L. | last2 = Coury | first2 = B. G. | last3 = Tengs | first3 = T. O. | last4 = Duffy | first4 = S. A. | year = 1989 | title = Minimizing the time to search visual displays: The role of highlighting | url = | journal = Human Factors: The Journal of the Human Factors and Ergonomics Society | volume = 31 | issue = 2| pages = 167–182 | doi = 10.1177/001872088903100206 | pmid = 2744770 }}</ref> Because visual search is an essential aspect of many tasks, visual search models are now developed in the context of integrating modeling systems. For example, Fleetwood and Byrne (2006) developed an ACT-R model of visual search through a display of labeled icons - predicting the effects of icon quality and set size not only on search time but on eye movements.<ref name=":1" /><ref>{{cite journal | last1 = Fleetwood | first1 = M. D. | last2 = Byrne | first2 = M. D. | year = 2006 | title = Modeling the visual search of displays: a revised ACT-R model of icon search based on eye-tracking data | url = | journal = Human-Computer Interaction | volume = 21 | issue = 2| pages = 153–197 | doi=10.1207/s15327051hci2102_1}}</ref>

==== Visual Sampling ====