You think you know where you looked? You better look again
Open accessAbstract
People are surprisingly bad at knowing where they have looked in a scene. We tested participants' ability to recall their own eye movements in 2 experiments using natural or artificial scenes. In each experiment, participants performed a change-detection (Exp.1) or search (Exp.2) task. On 25% of trials, after 3 seconds of viewing the scene, participants were asked to indicate where they thought they had just fixated. They responded by making mouse clicks on 12 locations in the unchanged scene. After 135 trials, observers saw 10 new scenes and were asked to put 12 clicks where they thought someone else would have looked. Although observers located their own fixations more successfully than a random model, their performance was no better than when they were guessing someone else's fixations. Performance with artificial scenes was worse, though judging one's own fixations was slightly superior. Even after repeating the fixation-location task on 30 scenes immediately after scene viewing, performance was far from the prediction of an ideal observer. Memory for our own fixation locations appears to add next to nothing beyond what common sense tells us about the likely fixations of others. These results have important implications for socially important visual search tasks. For example, a radiologist might think he has looked at "everything" in an image, but eye tracking data suggest that this is not so. Such shortcomings might be avoided by providing observers with better insights of where they have looked. (PsycINFO Database Record
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Human memory for already sampled locations is poor, resulting in less efficient and defective search behavior.
“However, human memory for already sampled locations proved to be poor, resulting in both less efficient and defective search behavior: less efficient because they may look multiple times at the same location, defective because they may miss a significant proportion of the image [19 , 21 , 22] .”
From Enhancing human-AI collaboration: The case of colonoscopy (2024) · cites this paper as [21]
The Abstract and Discussion report poor memory for one's own fixation locations and discuss the possibility that substantial areas of an image go unexamined. They do not establish that this memory failure causes people to revisit the same locations or makes search less efficient; the image-coverage concern is presented as an applied implication, not a measured effect of the experiments. (LLM, conf=0.85)
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Our Eyes do Not Always Go Where we Want Them to Go: Capture of the Eyes by New Objects
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Using cognitive psychology research to inform professional visual search operations
Biggs, A. T., Kramer, M. R., & Mitroff, S. R. (2018) · Journal of Applied Research in Memory and Cognition · doi:10.1016/j.jarmac.2018.04.001 · Cited by 53 · see citing works
Enhancing human-AI collaboration: The case of colonoscopy
Introzzi, L., Zonca, J., Cabitza, F., Cherubini, P., & Reverberi, C. (2024) · Digestive and Liver Disease · doi:10.1016/j.dld.2023.10.018 · Cited by 28 · see citing works
- Authors
- Võ, M. L.-H., Aizenman, A. M., & Wolfe, J. M.
- Affiliations
- Goethe University Frankfurt (DE)
- Brigham and Women's Hospital (US)
- Venue
- Journal of Experimental Psychology: Human Perception and Performance
- Published
- 2016-10
- Volume
- 42
- Issue
- 10
- Pages
- 1477-1481
- ISSN
- 0096-1523 (ISSN-L)
- 1939-1277
- PMC
- PMC5079107
- OpenAlex
- W2525103930
- Cited by
- 75
- References
- 1
- Citations by year
- 2026: 6 · 2025: 9 · 2024: 5 · 2023: 9 · 2022: 9 · 2021: 11 · 2020: 5 · 2019: 7 · 2018: 5 · 2017: 9
- FWCI
- 4.22
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Locations
- Journal of Experimental Psychology Human Perception & Performance (publishedVersion, other-oa)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institutes of Health (EY017001)
- Deutsche Forschungsgemeinschaft (VO 1683/2-1)
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Visual Attention and Saliency Detection
- Life Sciences › Neuroscience › Cognitive Neuroscience › Visual perception and processing mechanisms
- Life Sciences › Neuroscience › Cognitive Neuroscience › Memory Processes and Influences
- Keywords
- change detection, visual search, natural images, ideal observer, visual attention
- MeSH terms
- Metacognition, Adult, Eye Movements, Female, Fixation, Ocular, Humans, Male, Pattern Recognition, Visual, Eye Movement Measurements, Young Adult
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