Individual differences predict low prevalence visual search performance and sources of errors: An eye-tracking study.

2020 ◽  
Vol 26 (4) ◽  
pp. 646-658
Author(s):  
Chad Peltier ◽  
Mark W. Becker
2018 ◽  
Author(s):  
Alasdair D F Clarke ◽  
Jessica Irons ◽  
Warren James ◽  
Andrew B. Leber ◽  
Amelia R. Hunt

A striking range of individual differences has recently been reported in three different visual search tasks. These differences in performance can be attributed to strategy, that is, the efficiency with which participants control their search to complete the task quickly and accurately. Here we ask if an individual's strategy and performance in one search task is correlated with how they perform in the other two. We tested 64 observers in the three tasks mentioned above over two sessions. Even though the test-retest reliability of the tasks is high, an observer's performance and strategy in one task did not reliably predict their behaviour in the other two. These results suggest search strategies are stable over time, but context-specific. To understand visual search we therefore need to account not only for differences between individuals, but also how individuals interact with the search task and context. These context-specific but stable individual differences in strategy can account for a substantial proportion of variability in search performance.


Author(s):  
Kaifeng Liu ◽  
Calvin Ka-lun Or

This is an eye-tracking study examining the effects of image segmentation and target number on visual search performance. A two-way repeated-measures computer-based visual search test was used for data collection. Thirty students participated in the test, in which they were asked to search for all of the Landolt Cs in 80 arrays of closed rings. The dependent variables were search time, accuracy, fixation count, and average fixation duration. Our principal findings were that some of the segmentation methods significantly improved accuracy, and reduced search time, fixation count, and average fixation duration, compared with the no-segmentation condition. Increased target number was found to be associated with longer search time, lower accuracy, more fixations, and longer average fixation duration. Our study indicates that although visual search tasks with multiple targets are relatively difficult, the visual search accuracy and efficiency can potentially be improved with the aid of image segmentation.


Author(s):  
Laura E. Matzen ◽  
Mallory C. Stites ◽  
Zoe. N. Gastelum

AbstractEye tracking is a useful tool for studying human cognition, both in the laboratory and in real-world applications. However, there are cases in which eye tracking is not possible, such as in high-security environments where recording devices cannot be introduced. After facing this challenge in our own work, we sought to test the effectiveness of using artificial foveation as an alternative to eye tracking for studying visual search performance. Two groups of participants completed the same list comparison task, which was a computer-based task designed to mimic an inventory verification process that is commonly performed by international nuclear safeguards inspectors. We manipulated the way in which the items on the inventory list were ordered and color coded. For the eye tracking group, an eye tracker was used to assess the order in which participants viewed the items and the number of fixations per trial in each list condition. For the artificial foveation group, the items were covered with a blurry mask except when participants moused over them. We tracked the order in which participants viewed the items by moving their mouse and the number of items viewed per trial in each list condition. We observed the same overall pattern of performance for the various list display conditions, regardless of the method. However, participants were much slower to complete the task when using artificial foveation and had more variability in their accuracy. Our results indicate that the artificial foveation method can reveal the same pattern of differences across conditions as eye tracking, but it can also impact participants’ task performance.


2021 ◽  
Vol 21 (9) ◽  
pp. 1913
Author(s):  
Ines Verissimo ◽  
Stefanie Holsken ◽  
Christian NL Olivers

2021 ◽  
Vol 21 (5) ◽  
pp. 29
Author(s):  
Inês S. Veríssimo ◽  
Stefanie Hölsken ◽  
Christian N. L. Olivers

2021 ◽  
Author(s):  
Thomas L. Botch ◽  
Brenda D. Garcia ◽  
Yeo Bi Choi ◽  
Caroline E. Robertson

Visual search is a universal human activity in naturalistic environments. Traditionally, visual search is investigated under tightly controlled conditions, where head-restricted participants locate a minimalistic target in a cluttered array presented on a computer screen. Do classic findings of visual search extend to naturalistic settings, where participants actively explore complex, real-world scenes? Here, we leverage advances in virtual reality (VR) technology to relate individual differences in classic visual search paradigms to naturalistic search behavior. In a naturalistic visual search task, participants looked for an object within their environment via a combination of head-turns and eye-movements using a head-mounted display. Then, in a classic visual search task, participants searched for a target within a simple array of colored letters using only eye-movements. We tested how set size, a property known to limit visual search within computer displays, predicts the efficiency of search behavior inside immersive, real-world scenes that vary in levels of visual clutter. We found that participants' search performance was impacted by the level of visual clutter within real-world scenes. Critically, we also observed that individual differences in visual search efficiency in classic search predicted efficiency in real-world search, but only when the comparison was limited to the forward-facing field of view for real-world search. These results demonstrate that set size is a reliable predictor of individual performance across computer-based and active, real-world visual search behavior.


2012 ◽  
Vol 107 (3) ◽  
pp. 468-477 ◽  
Author(s):  
Giacomo Veneri ◽  
Elena Pretegiani ◽  
Francesca Rosini ◽  
Pamela Federighi ◽  
Antonio Federico ◽  
...  

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