1932

Abstract

In visual search tasks, observers look for targets among distractors. In the lab, this often takes the form of multiple searches for a simple shape that may or may not be present among other items scattered at random on a computer screen (e.g., Find a red T among other letters that are either black or red.). In the real world, observers may search for multiple classes of target in complex scenes that occur only once (e.g., As I emerge from the subway, can I find lunch, my friend, and a street sign in the scene before me?). This article reviews work on how search is guided intelligently. I ask how serial and parallel processes collaborate in visual search, describe the distinction between search templates in working memory and target templates in long-term memory, and consider how searches are terminated.

Loading

Article metrics loading...

/content/journals/10.1146/annurev-vision-091718-015048
2020-09-15
2024-06-19
Loading full text...

Full text loading...

/deliver/fulltext/vision/6/1/annurev-vision-091718-015048.html?itemId=/content/journals/10.1146/annurev-vision-091718-015048&mimeType=html&fmt=ahah

Literature Cited

  1. Adams WJ. 2008. Frames of reference for the light-from-above prior in visual search and shape judgements. Cognition 107:137–50
    [Google Scholar]
  2. Anderson BA. 2014. On the precision of goal-directed attentional selection. J. Exp. Psychol. Hum. Percept. Perform. 40:1755–62
    [Google Scholar]
  3. Anderson BA, Laurent PA, Yantis S 2011. Value-driven attentional capture. PNAS 108:10367–71
    [Google Scholar]
  4. Ásgeirsson ÁG, Kristjánsson Á 2019. Attentional priming does not enable observers to ignore salient distractors. Vis. Cogn. 27:595–608
    [Google Scholar]
  5. Awh E, Belopolsky AV, Theeuwes J 2012. Top-down versus bottom-up attentional control: a failed theoretical dichotomy. Trends Cogn. Sci. 16:437–43
    [Google Scholar]
  6. Bacon WF, Egeth HE. 1994. Overriding stimulus-driven attentional capture. Percept. Psychophys. 55:485–96
    [Google Scholar]
  7. Baldassi S, Verghese P. 2002. Comparing integration rules in visual search. J. Vis. 2:559–70
    [Google Scholar]
  8. Bauer B, Jolicœur P, Cowan WB 1996. Visual search for colour targets that are or are not linearly-separable from distractors. Vis. Res. 36:1439–66
    [Google Scholar]
  9. Beck VM, Hollingworth A, Luck SJ 2011. Simultaneous control of attention by multiple working memory representations. Psychol. Sci. 23:887–98
    [Google Scholar]
  10. Becker S, Atalla M, Folk CL 2020. Conjunction search: Can we simultaneously bias attention to features and relations. Atten. Percept. Psychophys. 82:246–68
    [Google Scholar]
  11. Becker SI. 2010. The role of target-distractor relationships in guiding attention and the eyes in visual search. J. Exp. Psychol. Gen. 139:247–65
    [Google Scholar]
  12. Belopolsky AV, Theeuwes J. 2012. Updating the premotor theory: The allocation of attention is not always accompanied by saccade preparation. J. Exp. Psychol. Hum. Percept. Perform. 38:902–14
    [Google Scholar]
  13. Berbaum KS, Franken EA, Caldwell RT, Shartz K, Madsen M 2019. Satisfaction of search in radiology. The Handbook of Medical Image Perception and Techniques E Samei, EA Krupinski 121–66 Cambridge, UK: Cambridge Univ. Press. , 2nd ed..
    [Google Scholar]
  14. Berbaum KS, Franken EA Jr., Dorfman DD, Rooholamini SA, Coffman CE et al. 1991. Time course of satisfaction of search. Invest. Radiol. 26:640–48
    [Google Scholar]
  15. Biederman I, Glass AL, Stacy EW 1973. Searching for objects in real-world scenes. J. Exp. Psychol. 97:22–27
    [Google Scholar]
  16. Boettcher SEP, Draschkow D, Dienhart E, MLH 2018. Anchoring visual search in scenes: assessing the role of anchor objects on eye movements during visual search. J. Vis. 18:11
    [Google Scholar]
  17. Brams S, Ziv G, Levin O, Spitz J, Wagemans J et al. 2019. The relationship between gaze behavior, expertise, and performance: a systematic review. Psychol. Bull. 145:10980–1027
    [Google Scholar]
  18. Brascamp JW, Pels E, Kristjansson A 2011. Priming of pop-out on multiple time scales during visual search. Vis. Res. 51:1972–78
    [Google Scholar]
  19. Bravo MJ, Farid H. 2014. Informative cues can slow search: the cost of matching a specific template. Attention Percept. Psychophys. 76:32–39
    [Google Scholar]
  20. Bravo MJ, Farid H. 2016. Observers change their target template based on expected context. Atten. Percept. Psychophys. 78:829–37
    [Google Scholar]
  21. Buetti S, Xu J, Lleras A 2019. Predicting how color and shape combine in the human visual system to direct attention. Sci. Rep. 9:20258
    [Google Scholar]
  22. Cain MS, Adamo SH, Mitroff SR 2013. A taxonomy of errors in multiple-target visual search. Vis. Cogn. 21:899–921
    [Google Scholar]
  23. Castelhano M, Heaven C. 2011. Scene context influences without scene gist: eye movements guided by spatial associations in visual search. Psychon. Bull. Rev. 18:890–96
    [Google Scholar]
  24. Castelhano MS, Henderson JM. 2007. Initial scene representations facilitate eye movement guidance in visual search. J. Exp. Psychol. Hum. Percept. Perform. 33:753–63
    [Google Scholar]
  25. Cave KR, Bush WS, Taylor TGG 2010. Split attention as part of a flexible attentional system for complex scenes: comment on Jans, Peters, and De Weerd 2010. Psychol. Rev. 117:685–95
    [Google Scholar]
  26. Chan LK, Hayward WG. 2014. No attentional capture for simple visual search: evidence for a dual-route account. J. Exp. Psychol. Hum. Percept. Perform. 40:2154–66
    [Google Scholar]
  27. Chan LKH, Hayward WG. 2009. Feature integration theory revisited: dissociating feature detection and attentional guidance in visual search. J. Exp. Psychol. Hum. Percept. Perform. 35:119–32
    [Google Scholar]
  28. Charnov EL. 1976. Optimal foraging, the marginal value theorem. Theor. Popul. Biol. 9:129–36
    [Google Scholar]
  29. Chun M, Jiang Y. 1998. Contextual cueing: Implicit learning and memory of visual context guides spatial attention. Cogn. Psychol. 36:28–71
    [Google Scholar]
  30. Chun MM, Wolfe JM. 1996. Just say no: How are visual searches terminated when there is no target present. Cogn. Psychol. 30:39–78
    [Google Scholar]
  31. Cousineau D, Shiffrin RM. 2004. Termination of a visual search with large display size effects. Spat. Vis. 17:327–52
    [Google Scholar]
  32. Cowan N. 1995. Attention and Memory: An Integrated Framework Oxford, UK: Oxford Univ. Press
    [Google Scholar]
  33. Cowan N. 2001. The magical number 4 in short-term memory: a reconsideration of mental storage capacity. Behav. Brain Sci. 24:87–114
    [Google Scholar]
  34. Cunningham CA, Egeth HE. 2016. Taming the white bear: initial costs and eventual benefits of distractor inhibition. Psychol. Sci. 27:476–85
    [Google Scholar]
  35. Cunningham CA, Wolfe JM. 2014. The role of object categories in hybrid visual and memory search. J. Exp. Psychol. Gen. 143:1585–99
    [Google Scholar]
  36. Desimone R, Duncan J. 1995. Neural mechanisms of selective visual attention. Annu. Rev. Neurosci. 18:193–222
    [Google Scholar]
  37. Dickinson CA, Zelinsky GJ. 2005. Marking rejected distractors: a gaze-contingent technique for measuring memory during search. Psychon. Bull. Rev. 12:1120–26
    [Google Scholar]
  38. Dowd EW, Mitroff SR. 2013. Attentional guidance by working memory overrides saliency cues in visual search. J. Exp. Psychol. Hum. Percept. Perform. 39:1786–96
    [Google Scholar]
  39. Drew T, Boettcher SP, Wolfe JM 2015. Searching while loaded: Visual working memory does not interfere with hybrid search efficiency but hybrid search uses working memory capacity. Psychon. Bull. Rev. 23:201–12
    [Google Scholar]
  40. Eckstein M, Koehler K, Welbourne LE, Akbas EP 2017. Humans but not deep neural networks often miss giant targets in scenes. Curr. Biol. 27:2827–32.e3
    [Google Scholar]
  41. Egeth H. 1977. Attention and preattention. The Psychology of Learning and Motivation GH Bower 277–320 New York: Academic
    [Google Scholar]
  42. Egeth HE, Virzi RA, Garbart H 1984. Searching for conjunctively defined targets. J. Exp. Psychol. Hum. Percept. Perform. 10:32–39
    [Google Scholar]
  43. Ehinger KA, Hidalgo-Sotelo B, Torralba A, Oliva A 2009. Modeling search for people in 900 scenes: a combined source model of eye guidance. Vis. Cogn. 17:945–78
    [Google Scholar]
  44. Enns JT, Rensink RA. 1990. Influence of scene-based properties on visual search. Science 247:721–23
    [Google Scholar]
  45. Evans KK, Birdwell RL, Wolfe JM 2013. If you don't find it often, you often don't find it: why some cancers are missed in breast cancer screening. PLOS ONE 8:5e64366
    [Google Scholar]
  46. Failing M, Theeuwes J. 2017. Selection history: how reward modulates selectivity of visual attention. Psychon. Bull. Rev. 25:514–38
    [Google Scholar]
  47. Fecteau JH, Munoz DP. 2006. Salience, relevance, and firing: a priority map for target selection. Trends Cogn. Sci. 10:382–90
    [Google Scholar]
  48. Foster DH, Ward PA. 1991. Horizontal-vertical filters in early vision predict anomalous line-orientation frequencies. Proc. R. Soc. Lond. B 243:83–86
    [Google Scholar]
  49. Frintrop S, Rome E, Christensen HI 2010. Computational visual attention systems and their cognitive foundations: a survey. ACM Trans. Appl. Percept. 7:6
    [Google Scholar]
  50. Gaspelin N, Vecera S. 2019. An introduction to the special issue on “Dealing with Distractors in Visual Search. .” Vis. Cogn. 27:183–84
    [Google Scholar]
  51. Ghazizadeh A, Griggs W, Hikosaka O 2016. Object-finding skill created by repeated reward experience. J. Vis. 16:17
    [Google Scholar]
  52. Green BF, Anderson LK. 1956. Color coding in a visual search task. J. Exp. Psychol. 51:19–24
    [Google Scholar]
  53. Greene MR, Oliva A. 2009. The briefest of glances: the time course of natural scene understanding. Psychol. Sci. 20:464–72
    [Google Scholar]
  54. Grubert A, Eimer M. 2018. The time course of target template activation processes during preparation for visual search. J. Neurosci. 38:9527–38
    [Google Scholar]
  55. Gunseli E, Meeter M, Olivers CNL 2014. Is a search template an ordinary working memory? Comparing electrophysiological markers of working memory maintenance for visual search and recognition. Neuropsychologia 60:29–38
    [Google Scholar]
  56. Hamker FH. 2004. A dynamic model of how feature cues guide spatial attention. Vis. Res. 44:501–21
    [Google Scholar]
  57. Helmholtz HV. 1924. Treatise on Physiological Optics Rochester, NY: Opt. Soc. Am.
    [Google Scholar]
  58. Henderson JM, Ferreira F. 2004. Scene perception for psycholinguists. The Interface of Language, Vision, and Action: Eye Movements and the Visual World JM Henderson, F Ferreira 1–58 New York: Psychol. Press
    [Google Scholar]
  59. Henderson JM, Hayes TR. 2017. Meaning guides attention in real-world scenes. Nat. Hum. Behav. 1:743–47
    [Google Scholar]
  60. Henderson JM, Hayes TR. 2018. Meaning guides attention in real-world scene images: evidence from eye movements and meaning maps. J. Vis. 18:10
    [Google Scholar]
  61. Hickey C, Chelazzi L, Theeuwes J 2010. Reward changes salience in human vision via the anterior cingulate. J. Neurosci. 30:11096–103
    [Google Scholar]
  62. Hillstrom AP. 2000. Repetition effects in visual search. Percept. Psychophys. 62:800–17
    [Google Scholar]
  63. Hoffman JE. 1979. A two-stage model of visual search. Percept. Psychophys. 25:319–27
    [Google Scholar]
  64. Hoffman JE. 1996. Visual attention and eye movements. Attention H Pashler 119–54 London: Univ. Coll. Lond. Press
    [Google Scholar]
  65. Horowitz TS. 2017. Prevalence in visual search: from the clinic to the lab and back again. Jpn. Psychol. Res. 59:65–108
    [Google Scholar]
  66. Horowitz TS, Wolfe JM. 1998. Visual search has no memory. Nature 394:575–77
    [Google Scholar]
  67. Horowitz TS, Wolfe JM. 2001. Search for multiple targets: Remember the targets, forget the search. Percept. Psychophys. 63:272–85
    [Google Scholar]
  68. Horowitz TS, Wolfe JM. 2003. Memory for rejected distractors in visual search. Vis. Cogn. 10:257–98
    [Google Scholar]
  69. Huang L, Holcombe AO, Pashler H 2004. Repetition priming in visual search: episodic retrieval, not feature priming. Mem. Cogn. 32:12–20
    [Google Scholar]
  70. Hubner R. 2001. A formal version of the Guided Search (GS2) model. Percept. Psychophys. 63:945–51
    [Google Scholar]
  71. Hulleman J, Olivers CNL. 2017. The impending demise of the item in visual search. Behav. Brain Sci. 40:e132
    [Google Scholar]
  72. Itti L, Koch C. 2000. A saliency-based search mechanism for overt and covert shifts of visual attention. Vis. Res. 40:1489–506
    [Google Scholar]
  73. Itti L, Koch C. 2001. Computational modelling of visual attention. Nat. Rev. Neurosci. 2:194–203
    [Google Scholar]
  74. Itti L, Koch C, Niebur E 1998. A model of saliency-based visual attention for rapid scene analysis. IEEE Trans. Pattern Anal. Mach. Intell. 20:1254–59
    [Google Scholar]
  75. Jackson SL, Cook AJ, Miglioretti DL, Carney PA, Geller BM et al. 2012. Are radiologists’ goals for mammography accuracy consistent with published recommendations. Acad. Radiol. 19:289–95
    [Google Scholar]
  76. Jans B, Peters JC, De Weerd P 2010. Visual spatial attention to multiple locations at once: The jury is still out. Psychol. Rev. 117:637–82
    [Google Scholar]
  77. Jiang YV, Won B-Y, Swallow KM, Mussack DM 2014. Spatial reference frame of attention in a large outdoor environment. J. Exp. Psychol. Hum. Percept. Perform. 40:1346–57
    [Google Scholar]
  78. Jonides J, Yantis S. 1988. Uniqueness of abrupt visual onset in capturing attention. Percept. Psychophys. 43:346–54
    [Google Scholar]
  79. Jung K, Han SW, Min Y 2019. Search efficiency is not sufficient: The nature of search modulates stimulus-driven attention. Atten. Percept. Psychophys. 81:61–70
    [Google Scholar]
  80. Kerzel D. 2019. The precision of attentional selection is far worse than the precision of the underlying memory representation. Cognition 186:20–31
    [Google Scholar]
  81. Kim H, Anderson BA. 2018. Dissociable components of experience-driven attention. Curr. Biol. 29:841–45.e2
    [Google Scholar]
  82. Kingsley HL. 1932. An experimental study of ‘search. .’ Am. J. Psychol. 44:314–18
    [Google Scholar]
  83. Klein R. 1988. Inhibitory tagging system facilitates visual search. Nature 334:430–31
    [Google Scholar]
  84. Klein R, Farrell M. 1989. Search performance without eye movements. Percept. Psychophys. 46:476–82
    [Google Scholar]
  85. Klein RM, MacInnes WJ. 1999. Inhibition of return is a foraging facilitator in visual search. Psychol. Sci. 10:346–52
    [Google Scholar]
  86. Koch C, Ullman S. 1985. Shifts in selective visual attention: towards the underlying neural circuitry. Hum. Neurobiol. 4:219–27
    [Google Scholar]
  87. Kowler E, Anderson E, Dosher B, Blaser E 1995. The role of attention in the programming of saccades. Vis. Res. 35:1897–916
    [Google Scholar]
  88. Kriegeskorte N. 2015. Deep neural networks: a new framework for modeling biological vision and brain information processing. Annu. Rev. Vis. Sci. 1:417–46
    [Google Scholar]
  89. Kristjansson A. 2006. Simultaneous priming along multiple feature dimensions in a visual search task. Vis. Res. 46:2554–70
    [Google Scholar]
  90. Kristjánsson Á, Egeth HE. 2020. How feature integration theory integrated cognitive psychology, neurophysiology, and psychophysics. Atten. Percept. Psychophys. 82:7–23
    [Google Scholar]
  91. Kristjánsson T, Thornton IM, Kristjánsson Á 2018. Time limits during visual foraging reveal flexible working memory templates. J. Exp. Psychol. Hum. Percept. Perform. 44:827–35
    [Google Scholar]
  92. Kruijne W, Meeter M. 2015. The long and the short of priming in visual search. Atten. Percept. Psychophys. 77:1558–73
    [Google Scholar]
  93. Lamy D, Antebi C, Aviani N, Carmel T 2008. Priming of pop-out provides reliable measures of target activation and distractor inhibition in selective attention. Vis. Res. 48:30–41
    [Google Scholar]
  94. Lamy D, Yashar A, Ruderman L 2013. Orientation search is mediated by distractor suppression: evidence from priming of pop-out. Vis. Res. 81:29–35
    [Google Scholar]
  95. Li Z. 2002. A salience map in primary visual cortex. Trends Cogn. Sci. 6:9–16
    [Google Scholar]
  96. Liesefeld HR, Müller HJ. 2019. Distractor handling via dimension weighting. Curr. Opin. Psychol. 29:160–67
    [Google Scholar]
  97. Liesefeld H, Müller HJ. 2020. A theoretical attempt to revive the serial/parallel-search dichotomy. Atten. Percept. Psychophys. 82:228–245
    [Google Scholar]
  98. Lleras A, Wang Z, Ng GJP, Ballew K, Xu J, Buetti S 2020. A target contrast signal theory of parallel processing in goal-directed search. Atten. Percept. Psychophys. 82:394–425
    [Google Scholar]
  99. Maljkovic V, Nakayama K. 1994. Priming of popout: I. Role of features. Mem. Cogn. 22:657–72
    [Google Scholar]
  100. McCarley JS, Wang RF, Kramer AF, Irwin DE, Peterson MS 2003. How much memory does oculomotor search have. Psychol. Sci. 14:422–26
    [Google Scholar]
  101. Miconi T, Groomes L, Kreiman G 2016. There's Waldo! A normalization model of visual search predicts single-trial human fixations in an object search task. Cereb. Cortex 26:3064–82
    [Google Scholar]
  102. Mitroff SR, Biggs AT, Adamo SH, Dowd EW, Winkle J, Clark K 2014. What can 1 billion trials tell us about visual search. J. Exp. Psychol. Hum. Percept. Perform. 41:1–5
    [Google Scholar]
  103. Moran R, Zehetleitner M, Liesefeld H, Müller H, Usher M 2015. Serial vs. parallel models of attention in visual search: accounting for benchmark RT-distributions. Psychon. Bull. Rev. 23:1300–15
    [Google Scholar]
  104. Moran R, Zehetleitner MH, Mueller HJ, Usher M 2013. Competitive guided search: meeting the challenge of benchmark RT distributions. J. Vis. 13:24
    [Google Scholar]
  105. Müller HJ, Heller D, Ziegler J 1995. Visual search for singleton feature targets within and across feature dimensions. Percept. Psychophys. 57:1–17
    [Google Scholar]
  106. Najemnik J, Geisler WS. 2009. Simple summation rule for optimal fixation selection in visual search. Vis. Res. 49:1286–94
    [Google Scholar]
  107. Navalpakkam V, Itti L. 2006. Top-down attention selection is fine grained. J. Vis. 6:1180–93
    [Google Scholar]
  108. Neider MB, Zelinsky GJ. 2008. Exploring set size effects in scenes: identifying the objects of search. Vis. Cogn. 16:1–10
    [Google Scholar]
  109. Neisser U. 1967. Cognitive Psychology New York: Appleton, Century, Crofts
    [Google Scholar]
  110. Neumann E, DeSchepper BG. 1991. Costs and benefits of target activation and distractor inhibition in selective attention. J. Exp. Psychol. Learn. Mem. Cogn. 17:1136–45
    [Google Scholar]
  111. Nobre AC, Kastner S. 2014. Oxford Handbook of Attention Oxford, UK: Oxford Univ. Press
    [Google Scholar]
  112. Nodine CF, Krupinski EA, Kundel HL, Toto L, Herman GT 1992. Satisfaction of search (SOS). Invest. Radiol. 27:571–73
    [Google Scholar]
  113. Nodine CF, Mello-Thoms C. 2019. Acquiring expertise in radiologic image interpretation. The Handbook of Medical Image Perception and Techniques E Samei, EA Krupinski 139–56 Cambridge, UK: Cambridge Univ. Press2nd ed.
    [Google Scholar]
  114. Oliva A. 2005. Gist of the scene. Neurobiology of Attention L Itti, G Rees, J Tsotsos 251–57 New York: Academic
    [Google Scholar]
  115. Oliva A, Torralba A. 2001. Modeling the shape of the scene: a holistic representation of the spatial envelope. Int. J. Comput. Vis. 42:145–75
    [Google Scholar]
  116. Olivers CN, Peters J, Houtkamp R, Roelfsema PR 2011. Different states in visual working memory: when it guides attention and when it does not. Trends Cogn. Sci. 15:327–34
    [Google Scholar]
  117. Palmer EM, Van Wert MJ, Horowitz TS, Wolfe JM 2019. Measuring the time course of selection during visual search. Atten. Percept. Psychophys. 81:47–60
    [Google Scholar]
  118. Palmer J. 1995. Attention in visual search: distinguishing four causes of a set size effect. Curr. Dir. Psychol. Sci. 4:118–23
    [Google Scholar]
  119. Palmer J, McLean J. 1995. Imperfect, unlimited-capacity, parallel search yields large set-size effects Paper presented at the Meeting of the Society for Mathematical Psychology Irvine, CA:
    [Google Scholar]
  120. Palmer J, Verghese P, Pavel M 2000. The psychophysics of visual search. Vis. Res. 40:1227–68
    [Google Scholar]
  121. Pereira EJ, Castelhano MS. 2014. Peripheral guidance in scenes: the interaction of scene context and object content. J. Exp. Psychol. Hum. Percept. Perform. 40:2056–72
    [Google Scholar]
  122. Pereira EJ, Castelhano MS. 2019. Attentional capture is contingent on scene region: using surface guidance framework to explore attentional mechanisms during search. Psychon. Bull. Rev. 26:1273–81
    [Google Scholar]
  123. Posner MI. 1980. Orienting of attention. Q. J. Exp. Psychol. 32:3–25
    [Google Scholar]
  124. Rajsic J, Ouslis NE, Wilson DE, Pratt J 2017. Looking sharp: Becoming a search template boosts precision and stability in visual working memory. Atten. Percept. Psychophys. 79:1643–51
    [Google Scholar]
  125. Rangelov D, Muller HJ, Zehetleitner M 2011. Dimension-specific intertrial priming effects are task-specific: evidence for multiple weighting systems. J. Exp. Psychol. Hum. Percept. Perform. 37:100–14
    [Google Scholar]
  126. Ratcliff R. 1978. A theory of memory retrieval. Psychol. Rev. 85:59–108
    [Google Scholar]
  127. Ratcliff R, McKoon G. 2008. The diffusion decision model: theory and data for two-choice decision tasks. Neural Comput 20:873–922
    [Google Scholar]
  128. Rensink RA. 2000. Seeing, sensing, and scrutinizing. Vis. Res. 40:1469–87
    [Google Scholar]
  129. Rizzolatti G, Riggio L, Dascola I, Umilta C 1987. Reorienting attention across the horizontal and vertical meridians: evidence in favor of a premotor theory of attention. Neuropsychologia 25:31–40
    [Google Scholar]
  130. Robbins CJ, Chapman P. 2018. Drivers’ visual search behavior toward vulnerable road users at junctions as a function of cycling experience. Hum. Factors 60:889–901
    [Google Scholar]
  131. Rosenholtz R, Huang J, Ehinger KA 2012. Rethinking the role of top-down attention in vision: effects attributable to a lossy representation in peripheral vision. Front. Psychol. 3:13
    [Google Scholar]
  132. Rosenholtz RE. 2011. What your visual system sees where you are not looking. Proc. SPIE: Human Vision and Electronic Imaging, XVI BE Rogowitz, TN Pappas, art. 786510 San Francisco, CA: SPIE
    [Google Scholar]
  133. Samei E, Krupinski EA 2018. The Handbook of Medical Image Perception and Techniques Cambridge, UK: Cambridge Univ. Press. , 2nd ed..
    [Google Scholar]
  134. Schill HM, Cain MS, Josephs EL, Wolfe JM 2020. Axis of rotation as a basic feature in visual search. Atten. Percept. Psychophys. 82:31–43
    [Google Scholar]
  135. Schwarz W, Miller JO. 2016. GSDT: an integrative model of visual search. J. Exp. Psychol. Hum. Percept. Perform. 42:1654–75
    [Google Scholar]
  136. Serences JT, Yantis S. 2006. Selective visual attention and perceptual coherence. Trends Cogn. Sci. 10:38–45
    [Google Scholar]
  137. Sharan L, Rosenholtz R, Adelson EH 2014. Accuracy and speed of material categorization in real-world images. J. Vis. 14:12
    [Google Scholar]
  138. Shi Z, Allenmark F, Zhu X, Elliott MA, Müller HJ 2020. To quit or not to quit in dynamic search. Atten. Percept. Psychophys. 82:799–817
    [Google Scholar]
  139. Soto D, Heinke D, Humphreys GW, Blanco MJ 2005. Early, involuntary top-down guidance of attention from working memory. J. Exp. Psychol. Hum. Percept. Perform. 31:248–61
    [Google Scholar]
  140. Sternberg S. 1966. High-speed scanning in human memory. Science 153:652–54
    [Google Scholar]
  141. Sully J. 1892. The Human Mind: A Text-Book of Psychology New York: D. Appleton & Co.
    [Google Scholar]
  142. Theeuwes J. 2013. Feature-based attention: It is all bottom-up priming. Philos. Trans. R. Soc. B 368:20130055
    [Google Scholar]
  143. Theeuwes J. 2018. Visual selection: usually fast and automatic; seldom slow and volitional. J. Cogn. 1:29
    [Google Scholar]
  144. Thorpe S, Fize D, Marlot C 1996. Speed of processing in the human visual system. Nature 381:520–52
    [Google Scholar]
  145. Treisman A. 1996. The binding problem. Curr. Opin. Neurobiol. 6:171–78
    [Google Scholar]
  146. Treisman A, Gelade G. 1980. A feature-integration theory of attention. Cogn. Psychol. 12:97–136
    [Google Scholar]
  147. Treue S. 2014. Object- and feature-based attention: monkey physiology. Oxford Handbook of Attention AC Nobre, S Kastner 573–600 Oxford, UK: Oxford Univ. Press
    [Google Scholar]
  148. Tsotsos J. 2011. A Computational Perspective on Visual Attention Cambridge, MA: MIT Press
    [Google Scholar]
  149. Tsotsos JK, Culhane SN, Wai WYK, Lai Y, Davis N, Nuflo F 1995. Modeling visual attention via selective tuning. Artif. Intell. 78:507–45
    [Google Scholar]
  150. Tsotsos JK, Eckstein MP, Landy MS 2015. Computational models of visual attention. Vis. Res. 116:Pt. B93–94
    [Google Scholar]
  151. Tuddenham WJ. 1962. Visual search, image organization, and reader error in roentgen diagnosis. Studies of the psycho-physiology of roentgen image perception. Radiology 78:694–704
    [Google Scholar]
  152. van Loon AM, Olmos-Solis K, Olivers CNL 2017. Subtle eye movement metrics reveal task-relevant representations prior to visual search. J. Vis. 17:13
    [Google Scholar]
  153. VanRullen R, Thorpe SJ. 2001. Is it a bird? Is it a plane? Ultra-rapid visual categorisation of natural and artifactual objects. Perception 30:655–68
    [Google Scholar]
  154. Verghese P. 2001. Visual search and attention: a signal detection approach. Neuron 31:523–35
    [Google Scholar]
  155. Vickery TJ, King L-W, Jiang Y 2005. Setting up the target template in visual search. J. Vis. 5:81–92
    [Google Scholar]
  156. Vo ML, Wolfe JM. 2013. Differential ERP signatures elicited by semantic and syntactic processing in scenes. Psychol. Sci. 24:1816–23
    [Google Scholar]
  157. Vo MLH, Henderson JM. 2009. Does gravity matter? Effects of semantic and syntactic inconsistencies on the allocation of attention during scene perception. J. Vis. 9:24
    [Google Scholar]
  158. von der Malsburg C. 1981. The correlation theory of brain function. Models of Neural Networks, Vol. II: Temporal Aspects of Coding and Information Processing in Biological Systems E Domany, JL van Hemmen, K Schulten 95–119 Berlin: Springer
    [Google Scholar]
  159. von Muhlenen A, Muller HJ, Muller D 2003. Sit-and-wait strategies in dynamic visual search. Psychol. Sci. 14:309–14
    [Google Scholar]
  160. Vul E, Rieth C, Lew TF, Rich AN 2020. The structure of illusory conjunctions reveals hierarchical binding of multi-part objects. Atten. Percept. Psychophys. 82:550–63
    [Google Scholar]
  161. Williams L, Drew T. 2019. What do we know about volumetric medical image search? A review of the basic science and medical image perception literatures. Cogn. Res. Princ. Implic. 4:21
    [Google Scholar]
  162. Wolfe JM. 1994. Guided Search 2.0: a revised model of visual search. Psychon. Bull. Rev. 1:202–38
    [Google Scholar]
  163. Wolfe JM. 1998a. Visual search. Attention H Pashler 13–74 Hove, UK: Psychol. Press
    [Google Scholar]
  164. Wolfe JM. 1998b. What do 1,000,000 trials tell us about visual search. Psychol. Sci. 9:33–39
    [Google Scholar]
  165. Wolfe JM. 2003. Moving towards solutions to some enduring controversies in visual search. Trends Cogn. Sci. 7:70–76
    [Google Scholar]
  166. Wolfe JM. 2007. Guided Search 4.0: current progress with a model of visual search. Integrated Models of Cognitive Systems W Gray 99–119 Oxford, UK: Oxford Univ. Press
    [Google Scholar]
  167. Wolfe JM. 2012. Saved by a log: How do humans perform hybrid visual and memory search. Psychol. Sci. 23:698–703
    [Google Scholar]
  168. Wolfe JM. 2013. When is it time to move to the next raspberry bush? Foraging rules in human visual search. J. Vis. 13:10
    [Google Scholar]
  169. Wolfe JM. 2014. Approaches to visual search: feature integration theory and guided search. Oxford Handbook of Attention AC Nobre, S Kastner 11–55 Oxford, UK: Oxford Univ. Press
    [Google Scholar]
  170. Wolfe JM. 2016. Use-inspired basic research in medical image perception. Cogn. Res. Princ. Implic. 1:17
    [Google Scholar]
  171. Wolfe JM. 2017. Visual attention: size matters. Curr. Biol. 27:R1002–3
    [Google Scholar]
  172. Wolfe JM. 2018. Visual search. Stevens’ Handbook of Experimental Psychology and Cognitive Neuroscience J Wixted 569–623 Hoboken, NJ: Wiley
    [Google Scholar]
  173. Wolfe JM, Alvarez GA, Rosenholtz R, Kuzmova YI, Sherman AM 2011a. Visual search for arbitrary objects in real scenes. Atten. Percept. Psychophys. 73:1650–71
    [Google Scholar]
  174. Wolfe JM, Brunelli DN, Rubinstein J, Horowitz TS 2013. Prevalence effects in newly trained airport checkpoint screeners: Trained observers miss rare targets, too. J. Vis. 13:33
    [Google Scholar]
  175. Wolfe JM, Butcher SJ, Lee C, Hyle M 2003. Changing your mind: on the contributions of top-down and bottom-up guidance in visual search for feature singletons. J. Exp. Psychol. Hum. Percept. Perform. 29:483–502
    [Google Scholar]
  176. Wolfe JM, Cain MS, Ehinger KA, Drew T 2015. Guided Search 5.0: meeting the challenge of hybrid search and multiple-target foraging Paper presented at the Annual Meeting of the Vision Science Society St. Petersburg, FL: May 15–20
    [Google Scholar]
  177. Wolfe JM, Cave KR, Franzel SL 1989. Guided Search: an alternative to the Feature Integration model for visual search. J. Exp. Psychol. Hum. Percept. Perform. 15:419–33
    [Google Scholar]
  178. Wolfe JM, Evans KK, Drew T 2018. The first moments of medical image perception. The Handbook of Medical Image Perception and Techniques E Samei, EA Krupinski 188–96 Cambridge, UK: Cambridge Univ. Press
    [Google Scholar]
  179. Wolfe JM, Friedman-Hill SR, Bilsky AB 1994. Parallel processing of part/whole information in visual search tasks. Percept. Psychophys. 55:537–50
    [Google Scholar]
  180. Wolfe JM, Friedman-Hill SR, Stewart MI, O'Connell KM 1992. The role of categorization in visual search for orientation. J. Exp. Psychol. Hum. Percept. Perform. 18:34–49
    [Google Scholar]
  181. Wolfe JM, Gancarz G. 1996. Guided Search 3.0: a model of visual search catches up with Jay Enoch 40 years later. Basic and Clinical Applications of Vision Science V Lakshminarayanan 189–92 Dordrecht, Neth.: Kluwer Acad.
    [Google Scholar]
  182. Wolfe JM, Horowitz TS. 2004. What attributes guide the deployment of visual attention and how do they do it. Nat. Rev. Neurosci. 5:495–501
    [Google Scholar]
  183. Wolfe JM, Horowitz TS. 2017. Five factors that guide attention in visual search. Nat. Hum. Behav. 1:0058
    [Google Scholar]
  184. Wolfe JM, Horowitz TS, Kenner NM 2005. Rare targets are often missed in visual search. Nature 435:439–40
    [Google Scholar]
  185. Wolfe JM, Horowitz TS, Palmer EM, Michod KO, VanWert MJ 2010a. Getting into Guided Search. Tutorials in Visual Cognition V Coltheart 93–120 Hove, UK: Psychol. Press
    [Google Scholar]
  186. Wolfe JM, Myers L. 2010. Fur in the midst of the waters: visual search for material type is inefficient. J. Vis. 10:8
    [Google Scholar]
  187. Wolfe JM, Palmer EM, Horowitz TS 2010b. Reaction time distributions constrain models of visual search. Vis. Res. 50:1304–11
    [Google Scholar]
  188. Wolfe JM, Van Wert MJ 2010. Varying target prevalence reveals two dissociable decision criteria in visual search. Curr. Biol. 20:121–24
    [Google Scholar]
  189. Wolfe JM, Vo ML, Evans KK, Greene MR 2011b. Visual search in scenes involves selective and nonselective pathways. Trends Cogn. Sci. 15:77–84
    [Google Scholar]
  190. Wu C-C, Wolfe JM. 2019. Eye movements in medical image perception: a selective review of past, present and future. Vision 3:32
    [Google Scholar]
  191. Yantis S. 1993. Stimulus-driven attentional capture. Curr. Dir. Psychol. Sci. 2:156–61
    [Google Scholar]
  192. Yu X, Geng JJ. 2019. The attentional template is shifted and asymmetrically sharpened by distractor context. J. Exp. Psychol. Hum. Percept. Perform. 45:336–53
    [Google Scholar]
  193. Zelinsky G. 2008. A theory of eye movements during target acquisition. Psychol. Rev. 115:787–835
    [Google Scholar]
  194. Zelinsky GJ, Sheinberg DL. 1997. Eye movements during parallel/serial visual search. J. Exp. Psychol. Hum. Percept. Perform. 23:244–62
    [Google Scholar]
  195. Zhang X, Huang J, Yigit-Elliott S, Rosenholtz R 2015. Cube search, revisited. J. Vis. 15:9
    [Google Scholar]
/content/journals/10.1146/annurev-vision-091718-015048
Loading
/content/journals/10.1146/annurev-vision-091718-015048
Loading

Data & Media loading...

  • Article Type: Review Article
This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error