DOI: 10.17586/1023-5086-2021-88-12-28-35
УДК: 612.84, 612.843.7, 004.93, 621.397.3
Optical search and visual expertise
Full text «Opticheskii Zhurnal»
Full text on elibrary.ru
Publication in Journal of Optical Technology
Скуратова К.А., Шелепин Е.Ю., Яровая Н.П. Оптический поиск и зрительный навык // Оптический журнал. 2021. Т. 88. № 12. С. 28–35. http://doi.org/10.17586/1023-5086-2021-88-12-28-35
Skuratova K.A., Shelepin E.Yu., Yarovaya N.P. Optical search and visual expertise [in Russian] // Opticheskii Zhurnal. 2021. V. 88. № 12. P. 28–35. http://doi.org/10.17586/1023-5086-2021-88-12-28-35
K. A. Skuratova, E. Yu. Shelepin, and N. P. Yarovaya, "Optical search and visual expertise," Journal of Optical Technology. 88(12), 700-705 (2021). https://doi.org/10.1364/JOT.88.000700
The eye movement parameters during a visual search for informative features in face images by a person and the identification of changes in these parameters depending on the expertise of this person were experimentally investigated to discover the effect of expertise in visual search required for the development of automated programs for the optical search for a target. The enhancement in the recognition of blurred images at the periphery of the visual field during the learning process is demonstrated for the first time. This process is the reason for the minimization of eye movement and, consequently, the time required for target search occurring with the accumulation of professional experience.
physiological optics, goal, optical search, eye movement, identification, learning, visual expertise
OCIS codes: 330.2210, 330.5020, 330.4270
References:1. S. E. Zdor and V. B. Shirokov, Optical Search and Recognition (Nauka, Moscow, 1973).
2. N. P. Travnikova, Effectiveness of Visual Search (Mashinostroenie, Moscow, 1985).
3. N. N. Krasil’nikov, Theory of Image Transfer and Perception (Radio i Svyaz’, Moscow, 1986).
4. Yu. E. Shelepin and N. N. Krasil’nikov, “Principle of least action, physiology of vision, and conditioned reflexes theory,” Russ. J. Physiol. 89(6), 725–730 (2003).
5. R. O. Malashin, “Principle of least action in dynamically configured image analysis systems,” J. Opt. Technol. 86(11), 678–685 (2019) [Opt. Zh. 86(11), 5–13 (2019)].
6. Yu. E. Shelepin, A. K. Kharauzov, O. V. Zhukova, S. V. Pronin, M. S. Kuprianov, and O. V. Tsvetkov, “Masking and detection of hidden signals in dynamic images,” J. Opt. Technol. 87(10), 624–632 (2020) [Opt. Zh. 87(10), 89–102 (2020)].
7. T. T. Brunyé, T. Drew, D. L. Weaver, and J. G. Elmore, “A review of eye tracking for understanding and improving diagnostic interpretation,” Cognit. Res. 4(1), 7 (2019).
8. N. P. Yarovaya, E. R. Araviiskaia, V. S. Zueva, K. A. Skuratova, and E. Yu. Shelepin, “The relationship between self-attitude and oculomotor patterns in self-face perception in women,” Russ. Psychol. J. 18(1), 22–33 (2021).
9. H. L. Kundel, C. F. Nodine, E. A. Krupinski, and C. Mello-Thoms, “Using gaze-tracking data and mixture distribution analysis to support a holistic model for the detection of cancers on mammograms,” Acad. Radiol. 15(7), 881–886 (2008).
10. R. S. Crowley, G. J. Naus, J. Stewart, and C. P. Friedman, “Development of visual diagnostic expertise in pathology: an information-processing study,” J. Am. Med. Inf. Assoc. 10, 39–51 (2003).
11. R. G. Swensson, “A two-stage detection model applied to skilled visual search by radiologists,” Percept. Psychophys. 27, 11–16 (1980).
12. N. Cowan, “The magical number 4 in short-term memory: a reconsideration of mental storage capacity,” Behav. Brain Sci. 24(1), 87–114 (2001).
13. S. F. Sergeev and A. V. Khomyakov, “Operator’s perception of groups of dynamic objects,” J. Opt. Technol. 88(6), 337–342 (2021) [Opt. Zh. 88(6), 68–75 (2021)].
14. J. M. Wolfe, M. L. Võ, K. K. Evans, and M. R. Greene, “Visual search in scenes involves selective and nonselective pathways,” Trends Cognit. Sci. 15(2), 77–84 (2011).
15. T. Drew, K. Evans, M. L. Võ, F. L. Jacobson, and J. M. Wolfe, “Informatics in radiology: what can you see in a single glance and how might this guide visual search in medical images?” Radiographics 33(1), 263–274 (2013).
16. F. Campbell and Yu. E. Shelepin, “Foveola capabilities in object recognition,” Sens. Sist. 4(2), 181–185 (1990).
17. H. Sheridan and E. M. Reingold, “Expert versus novice differences in the detection of relevant information during a chess game: evidence from eye movements,” Front. Psychol. 5, 941 (2014).
18. F. Gobet and H. A. Simon, “Templates in chess memory: a mechanism for recalling several boards,” Cognit. Psychol. 31(1), 1–40 (1996).
19. K. S. Maturi and H. Sheridan, “Expertise effects on attention and eye-movement control during visual search: evidence from the domain of music reading,” Atten. Percept. Psychophys. 82, 2201–2208 (2020).
20. R. A. Searston and J. M. Tangen, “The style of a stranger: identification expertise generalizes to coarser level categories,” Psychon. Bull. Rev. 24(4), 1324–1329 (2017).
21. T. T. Brunyé, P. A. Carney, K. H. Allison, L. G. Shapiro, D. L. Weaver, and J. G. Elmore, “Eye movements as an index of pathologist visual expertise: a pilot study,” PloS One 9(8), e103447 (2014).
22. S. Voisin, F. Pinto, G. Morin-Ducote, K. B. Hudson, and G. D. Tourassi, “Predicting diagnostic error in radiology via eye-tracking and image analytics: preliminary investigation in mammography,” Med. Phys. 40(10), 101906 (2013).
23. J. Shiraishi, Q. Li, D. Appelbaum, and K. Doi, “Computer-aided diagnosis and artificial intelligence in clinical imaging,” Semin. Nucl. Med. 41(6), 449–462 (2011).
24. R. O. Malashin, “Sparsely ensembled convolutional neural network classifiers via reinforcement learning,” in Proceedings of the 6th International Conference on Machine Learning Technologies (2021), pp. 102–110.