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When do I Quit? The Search Termination Problem in Visual Search

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The Influence of Attention, Learning, and Motivation on Visual Search

Part of the book series: Nebraska Symposium on Motivation ((NSM))

Abstract

In visual search tasks, observers look for targets in displays or scenes containing distracting, non-target items. Most of the research on this topic has concerned the finding of those targets. Search termination is a less thoroughly studied topic. When is it time to abandon the current search? The answer is fairly straight forward when the one and only target has been found (There are my keys.). The problem is more vexed if nothing has been found (When is it time to stop looking for a weapon at the airport checkpoint?) or when the number of targets is unknown (Have we found all the tumors?). This chapter reviews the development of ideas about quitting time in visual search and offers an outline of our current theory.

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References

  • Bacon, W. F., & Egeth, H. E. (1994). Overriding stimulus-driven attentional capture. Perception and Psychophysics, 55(5), 485–496.

    PubMed  Google Scholar 

  • Berbaum, K. S., Franken, E. A., Jr., Dorfman, D. D., Rooholamini, S. A., Kathol, M. H., & Barloon, T. J., et al. (1990). Satisfaction of search in diagnostic radiology. Investigative Radiology, 25(2), 133–140.

    PubMed  Google Scholar 

  • Berbaum, K. S., Franken, E. A., Jr., Dorfman, D. D., Caldwell, R. T., & Krupinski, E. A. (2000). Role of faulty decision making in the satisfaction of search effect in chest radiography. Academic Radiology, 7(12), 1098–1106.

    PubMed  Google Scholar 

  • Bravo, M. J., & Farid, H. (2004). Search for a category target in clutter. Perception, 33(5), 643–652.

    PubMed  Google Scholar 

  • Bravo, M. J., & Farid, H. (2008). A scale invariant measure of clutter. Journal of Vision, 8(1), 1–9.

    PubMed  Google Scholar 

  • Brown, S. D., & Heathcote, A. (2008). The simplest complete model of choice response time: Linear ballistic accumulation. Cognitive Psychology, 57(3), 153–178.

    PubMed  Google Scholar 

  • Buschman, T. J., & Miller, E. K. (2009). Serial, covert shifts of attention during visual search are reflected by the frontal eye fields and correlated with population oscillations. Neuron, 63, 386–396.

    PubMed  Google Scholar 

  • Charnov, E. L. (1976). Optimal foraging, the marginal value theorem. Theoretical Population Biology, 9, 129–136.

    PubMed  Google Scholar 

  • Chun, M. M., & Wolfe, J. M. (1996). Just say no: How are visual searches terminated when there is no target present? Cognitive Psychology, 30, 39–78.

    PubMed  Google Scholar 

  • Colquhoun, W. P., & Baddeley, A. D. (1967). Influence of signal probability during pretraining on vigilance decrement. Journal of Experimental Psychology: Human Perception and Performance, 73(1), 153–155.

    Google Scholar 

  • Dehaene, S. (1997). The number sense. New York, Cambridge: Oxford University Press, Penguin press.

    Google Scholar 

  • Dodd, M. D., Castel, A. D., & Pratt, J. (2003). Inhibition of return with rapid serial shifts of attention: Implications for memory and visual search. Perception & Psychophysics, 65(7), 1126–1135.

    Google Scholar 

  • Donkin, C., Brown, S., Heathcote, A., & Wagenmakers, E. -J. (2011). Diffusion versus linear ballistic accumulation: Different models but the same conclusions about psychological processes? Psychonomic Bulletin & Review, 18(1), 61–69.

    Google Scholar 

  • Dukas, R. (2002). Behavioural and ecological consequences of limited attention. Philosophical Transaction of the Royal Society London Series B: Biolgical Science, 357(1427), 1539–1547.

    Google Scholar 

  • Dukas, R. (2004). Causes and consequences of limited attention. Brain, Behavior and Evolution, 63(4), 197–210.

    PubMed  Google Scholar 

  • Duncan, J., & Humphreys, G. W. (1989). Visual search and stimulus similarity. Psychological Review, 96, 433–458.

    PubMed  Google Scholar 

  • Egeth, H. E., Virzi, R. A., & Garbart, H. (1984). Searching for conjunctively defined targets. Journal of Experimental Psychology: Human Perception and Performance, 10, 32–39.

    PubMed  Google Scholar 

  • Einhauser, W., Spain, M., & Perona, P. (2008). Objects predict fixations better than early saliency. Journal of Vision, 8(14), 1–26.

    Google Scholar 

  • Ethell, S. C., & Manning, D. (2001). Effects of prevalence on visual search and decision making in fracture detection. In E. A. Krupinski & D. P. Chakraborty (Eds.), Image perception and performance, proceedings of spie (Vol. 4324, pp. 249–257). SPIE.

    Google Scholar 

  • Felisberti, F. M., Solomon, J. A., & Morgan, M. J. (2005). The role of target salience in crowding. Perception, 34(7), 823–833.

    Google Scholar 

  • Fleck, M. S., & Mitroff, S. R. (2007). Rare targets are rarely missed in correctable search. Psychological science, 18(11), 943–947.

    PubMed  Google Scholar 

  • Fleck, M. S., Samei, E., & Mitroff, S. R. (2010). Generalized “satisfaction of search”: Adverse influences on dual-target search accuracy. Journal of Experimental Psychology: Applied, 16(1), 60–71. doi: 10.1037/a0018629.

    PubMed  Google Scholar 

  • Foulsham, T., & Underwood, G. (2008). What can saliency models predict about eye movements? Spatial and sequential aspects of fixations during encoding and recognition. Journal of Vision, 8(2), 6 1–17.

    PubMed  Google Scholar 

  • Franconeri, S. L., Hollingworth, A., & Simons, D. J. (2005). Do new objects capture attention? Psychological Science, 16(4), 275–281.

    PubMed  Google Scholar 

  • Friedman-Hill, S. R., & Wolfe, J. M. (1995). Second-order parallel processing: Visual search for the odd item in a subset. Journal of Experimental Psychology: Human Perception and Performance, 21(3), 531–551.

    PubMed  Google Scholar 

  • Gilchrist, I. D., & Harvey, M. (2006). Evidence for a systematic component within scanpaths in visual search. Visual Cognition, 14(5–7), 704–771.

    Google Scholar 

  • Godwin, H. J., Menneer, T., Cave, K. R., Helman, S., Way, R. L., & Donnelly, N. (2010). The impact of relative prevalence on dual-target search for threat items from airport X-ray screening. Acta Psychologica, 134(1), 79–84. doi: 10.1016/j.actpsy.2009.12.009.

    PubMed  Google Scholar 

  • Goldsmith, M. (1998). What’s in a location? Comparing object-based and space-based models of feature integration in visual search. Journal of Experimental Psychology: General, 127(2), 189–219.

    Google Scholar 

  • Greene, M. R., & Oliva, A. (2009). The briefest of glances: The time course of natural scene understanding. Psychological Science, 20(4), 464–472.

    PubMed  Google Scholar 

  • Gur, D., Rockette, H. E., Armfield, D. R., Blachar, A., Bogan, J. K., Brancatelli, G., et al. (2003). Prevalence effect in a laboratory environment. Radiology, 228(1), 10–14.

    PubMed  Google Scholar 

  • Hamid, S. N., Stankiewicz, B., & Hayhoe, M. (2010). Gaze patterns in navigation: Encoding information in large-scale environments. Journal of Vision, 10(12), 28.

    PubMed  Google Scholar 

  • Hamker, F. (2006). Modeling feature-based attention as an active top-down inference process Biosystems, 86(1–3), 91–99.

    PubMed  Google Scholar 

  • Healy, A. F., & Kubovy, M. (1981). Probability matching and the formation of conservative decision rules in a numerical analog of signal detection. Journal of Experimental Psychology: Human Learning and Memory, 7(5), 344–354.

    Google Scholar 

  • Hearns, J. F., & Moss, S. M. (1968). Effect of method of payoff on detection of targets in a visual search task. Journal of Experimental Psychology: Human Learning and Memory, 78(4P1), 569–573.

    Google Scholar 

  • Henderson, J. M., & Ferreira, F. (2004). Scene perception for psycholinguists. In J. M. Henderson & F. Ferreira (Eds.), The interface of language, vision, and action: Eye movements and the visual world (pp. 1–58). New York: Psychology.

    Google Scholar 

  • Hick, W. E. (1952). On the rate of gain of information. Quarterly Journal of Experimental Psychology, 4, 11–26.

    Google Scholar 

  • Hickey, C., & Theeuwes, J. (2008). Reward primes visual search. Perception, 37, 46–46.

    Google Scholar 

  • Hickey, C., Chelazzi, L., & Theeuwes, J. (2011). Reward has a residual impact on target selection in visual search, but not on the suppression of distractors. Visual Cognition, 19(1), 117–128.

    Google Scholar 

  • Horowitz, T. S., & Wolfe, J. M. (1998). Visual search has no memory. Nature, 394(Aug 6), 575–577.

    PubMed  Google Scholar 

  • Horowitz, T. S., & Wolfe, J. M. (2003). Memory for rejected distractors in visual search? Visual Cognition, 10(3), 257–298.

    Google Scholar 

  • Hyman, R. (1953). Stimulus information as a determinant of reaction time. Journal of Experimental Psychology: Human Learning and Memory, 45(3), 188–196.

    Google Scholar 

  • Ishibashi, K., Kita, S., & Wolfe, J. (2012). The effects of local prevalence and explicit expectations on search termination times. Attention, Perception, & Psychophysics, 74(1), 115–123.

    Google Scholar 

  • Jovancevic-Misic, J., & Hayhoe, M. (2009). Adaptive gaze control in natural environments. Journal of Neuroscience, 29(19), 6234–6238.

    PubMed  Google Scholar 

  • Klein, R. (1988). Inhibitory tagging system facilitates visual search. Nature, 334, 430–431.

    PubMed  Google Scholar 

  • Klein, R. M., & MacInnes, W. J. (1999). Inhibition of return is a foraging facilitator in visual search. Psychological Science, 10(July), 346–352.

    Google Scholar 

  • Koch, C., & Ullman, S. (1985). Shifts in selective visual attention: Towards the underlying neural circuitry. Human Neurobiology, 4, 219–227.

    PubMed  Google Scholar 

  • Kristjansson, A. (2000). In search of rememberance: Evidence for memory in visual search. Psychological Science, 11(4), 328–332.

    PubMed  Google Scholar 

  • Kristjansson, A., Sigurjonsdottir, O., & Driver, J. (2010). Fortune and reversals of fortune in visual search: Reward contingencies for pop-out targets affect search efficiency and target repetition effects. Attention Perception Psychophysics, 72(5), 1229–1236.

    Google Scholar 

  • Krueger, L. E. (1984). Perceived numerosity: A comparison of magnitude production, magnitude estimation, and discrimination judgments. Perception & Psychophysics, 35(6), 536–542.

    Google Scholar 

  • Kunar, M. A., Rich, A. N., & Wolfe, J. M. (2010). Spatial and temporal separation fails to counteract the effects of low prevalence in visual search. Visual Cognition, 18(6), 881–897.

    PubMed  Google Scholar 

  • Kundel, H. L. (1982). Disease prevalence and radiological decision making. Investigative Radiology, 17(1), 107–109.

    PubMed  Google Scholar 

  • Kundel, H. L. (2000). Disease prevalence and the index of detectability: A survey of studies of lung cancer detection by chest radiography. In E. A. Krupinski (Ed.), Medical imaging 2000: Image perception and performance (Vol. 3981, pp. 135–144). Society of Photo Optical.

    Google Scholar 

  • Lau, J. S., & Huang, L. (2010). The prevalence effect is determined by past experience, not future prospects. Vision Research, 50(15), 1469–1474.

    PubMed  Google Scholar 

  • Levi, D. M. (2008). Crowding-an essential bottleneck for object recognition: A mini-review. Vision Research, 48(5), 635–654.

    PubMed  Google Scholar 

  • Logan, G. D. (1996). The CODE theory of visual attention: An integration of space-based and object-based attention. Psychological Review, 103(4), 603–649.

    PubMed  Google Scholar 

  • Mackworth, J. (1970). Vigilance and attention. Harmondsworth: Penguin Books.

    Google Scholar 

  • Macmillan, N. A., & Creelman, C. D. (2005). Detection theory. Mahwah: Erlbaum.

    Google Scholar 

  • Maddox, W. T. (2002). Toward a unified theory of decision criterion learning in perceptual categorization. Journal of the Experimental Analysis of Behavior, 78(3), 567–595.

    PubMed  Google Scholar 

  • Maljkovic, V., & Martini, P. (2005). Implicit short-term memory and event frequency effects in visual search. Vision Research, 45(21), 2831–2846.

    PubMed  Google Scholar 

  • Maljkovic, V., & Nakayama, K. (1994). Priming of popout: I. Role of features. Memory & Cognition, 22(6), 657–672.

    Google Scholar 

  • Masciocchi, C. M., Mihalas, S., Parkhurst, D., & Niebur, E. (2009). Everyone knows what is interesting: Salient locations which should be fixated. Journal of Vision, 9(11), 1–22.

    PubMed  Google Scholar 

  • Nakayama, K., & Silverman, G. H. (1986). Serial and parallel processing of visual feature conjunctions. Nature, 320, 264–265.

    PubMed  Google Scholar 

  • Navalpakkam, V., Koch, C., & Perona, P. (2009). Homo economicus in visual search. Journal of Vision, 9(1), 31.

    PubMed  Google Scholar 

  • Neider, M. B., & Zelinsky, G. J. (2008). Exploring set size effects in scenes: Identifying the objects of search. Visual Cognition, 16(1), 1–10.

    Google Scholar 

  • Nodine, C. F., Krupinski, E. A., Kundel, H. L., Toto, L., & Herman, G. T. (1992). Satisfaction of search (SOS). Invest Radiology, 27(7), 571–573.

    Google Scholar 

  • Oliva, A. (2005). Gist of the scene. In L. Itti, G. Rees, & J. Tsotsos (Eds.), Neurobiology of attention (pp. 251–257). San Diego: Academic.

    Google Scholar 

  • Palmer, E. M., Horowitz, T. S., Torralba, A., & Wolfe, J. M. (2011). What are the shapes of response time distributions in visual search? Journal of Experimental Psychology: Human Perception and Performance, 37(1), 58–71.

    PubMed  Google Scholar 

  • Parasuraman, R., & Davies, D. R. (1976). Decision theory analysis of response latencies in vigilance. Journal of Experimental Psychology. Human Perception and Performance, 2(4), 578–590.

    PubMed  Google Scholar 

  • Peterson, M. S., Kramer, A. F., Wang, R. F., Irwin, D. E., & McCarley, J. S. (2001). Visual search has memory. Psychological Science, 12(4), 287–292.

    PubMed  Google Scholar 

  • Pyke, G. H., Pulliam, H. R., & Charnov, E. L. (1977). Optimal foraging: A selective review of theory and tests. The Quarterly Review of Biology, 52(2), 137–154.

    Google Scholar 

  • Ratcliff, R. (1978). A theory of memory retrieval. Psychology. Review, 85(2), 59–108.

    Google Scholar 

  • Rayner, K. (1983). Visual selection in reading, picture perception, and visual search. In H. Bouma & B. G. Bouwhuis (Eds.), Attention and performance X (Vol. 10, pp. 67–96). Hillside: Erlbaum.

    Google Scholar 

  • Reynolds, J. H., & Chelazzi, L. (2004). Attentional modulation of visual processing. Annual Review of Neuroscience, 27, 611–647.

    PubMed  Google Scholar 

  • Roelfsema, P. R., Lammer, V. A. F., & Spekreijse, H. (1998). Object-based attention in the primary visual cortex of the macaque monkey. Nature, 395, 376.

    PubMed  Google Scholar 

  • Rosenholtz, R., Chan, S., & Balas, B. (2009). A crowded model of visual search. Journal of Vision, 9(8), 1197–1197.

    Google Scholar 

  • Sagi, D. (1988). The combination of spatial frequency and orientation is effortlessly perceived. Perception and Psychophysics, 43, 601–603.

    PubMed  Google Scholar 

  • Sherman, A. M., Greene, M. R., & Wolfe, J. M. (2011). Depth and size information reduce effective set size for visual search in real-world scenes. Poster presented at the annual meeting of the Vision Sciences Society in Naples, FL., May, 2011

    Google Scholar 

  • Shore, D. I., & Klein, R. M. (2000). On the manifestations of memory in visual search. Spatial vision, 14(1), 59–75.

    PubMed  Google Scholar 

  • Stephens, D. W., & Krebs, J. R. (1986). Foraging theory. Princeton: Princeton University Press.

    Google Scholar 

  • Sternberg, S. (1966). High-speed scanning in human memory. Science, 153, 652–654.

    PubMed  Google Scholar 

  • Swets, J. A., & Kristofferson, A. B. (1970). Attention. Annual Review of Psychology, 21, 339–366.

    PubMed  Google Scholar 

  • Theeuwes, J. (1995). Abrupt luminance change pops out; abrupt color change does not. Perception & Psychophysics, 57(5), 637–644.

    Google Scholar 

  • Theeuwes, J. (2010). Top-down and bottom-up control of visual selection. Acta Psychologica, 135(2), 77–99. doi: 10.1016/j.actpsy.2010.02.006.

    PubMed  Google Scholar 

  • Theeuwes, J., & Kooi, J. L. (1994). Parallel search for a conjunction of shape and contrast polarity. Vision Research, 34(22), 3013–3016.

    PubMed  Google Scholar 

  • Torralba, A., Oliva, A., Castelhano, M. S., & Henderson, J. M. (2006). Contextual guidance of eye movements and attention in real-world scenes: The role of global features on object search. Psychological Review, 113(4), 766–786.

    PubMed  Google Scholar 

  • Treisman, A., & Gelade, G. (1980). A feature-integration theory of attention. Cognitive Psychology, 12, 97–136.

    PubMed  Google Scholar 

  • Trick, L. M., & Pylyshyn, Z. W. (1994). Why are small and large numbers enumerated differently? A limited-capacity preattentive stage in vision. Psychology. Review, 101(1), 80–102.

    Google Scholar 

  • Tsotsos, J. (2011). A computational perspective on visual attention. Cambridge: MIT Press.

    Google Scholar 

  • Van Zandt, T. (2002). Analysis of response time distributions. In H. Pashler, & J. Wixted (Eds.), Stevens’ handbook of experimental psychology (3rd edn), Methodology in experimental psychology (Vol. 4, pp. 461–516). New York: Wiley.

    Google Scholar 

  • Van Wert, M. J., Wolfe, J. M., & Horowitz, T. S. (2009). Even in correctable search, some types of rare targets are frequently missed. Attention, Perception & Psychophysics, 71(3), 541–553.

    Google Scholar 

  • Vlaskamp, B. N., & Hooge, I. T. (2006). Crowding degrades saccadic search performance. Vision Research, 46(3), 417–425.

    PubMed  Google Scholar 

  • Vo, M. L. H., & Henderson, J. M. (2009). Does gravity matter? Effects of semantic and syntactic inconsistencies on the allocation of attention during scene perception. Journal of Vision, 9(3), 1–15.

    PubMed  Google Scholar 

  • Vo, M. L.-H., & Henderson, J. M. (2010). The time course of initial scene processing for eye movement guidance in natural scene search. Journal of Vision, 10(3), 1–13.

    PubMed  Google Scholar 

  • von Muhlenen, A., Muller, H. J., & Muller, D. (2003). Sit-and-wait strategies in dynamic visual search. Psychol Science, 14(4), 309–314.

    Google Scholar 

  • Wolfe, J. M. (1994). Guided Search 2.0: A revised model of visual search. Psychonomic Bulletin and Review, 1(2), 202–238.

    Google Scholar 

  • Wolfe, J. M. (1998). What do 1,000,000 trials tell us about visual search? Psychological Science, 9(1), 33–39.

    Google Scholar 

  • Wolfe, J. M., & Horowitz, T. S. (2004). What attributes guide the deployment of visual attention and how do they do it? Nature Reviews Neuroscience, 5(6), 495–501.

    PubMed  Google Scholar 

  • Wolfe, J. M., & Van Wert, M. J. (2010). Varying target prevalence reveals two, dissociable decision criteria in visual search. Current Biology, 20(2), 121–124.

    PubMed  Google Scholar 

  • Wolfe, J. M., Cave, K. R., & Franzel, S. L. (1989). Guided Search: An alternative to the feature integration model for visual search. Journal of Experimental Psychology: Human Perception and Performance, 15, 419–433.

    PubMed  Google Scholar 

  • Wolfe, J., Horowitz, T., Kenner, N. M., Hyle, M., & Vasan, N. (2004). How fast can you change your mind? The speed of top-down guidance in visual search. Vision Research, 44(12), 1411–1426.

    PubMed  Google Scholar 

  • Wolfe, J. M., Horowitz, T. S., & Kenner, N. M. (2005). Rare items often missed in visual searches. Nature, 435, 439–440.

    PubMed  Google Scholar 

  • Wolfe, J. M., Horowitz, T. S., Van Wert, M. J., Kenner, N. M., Place, S. S., & Kibbi, N. (2007). Low target prevalence is a stubborn source of errors in visual search tasks. Journal of Experimental psychology: General, 136(4), 623–638.

    Google Scholar 

  • Wolfe, J., Alvarez, G., Rosenholtz, R., Oliva, A., Torralba, A., Kuzmova, Y., et al. (2008). Search for arbitrary objects in natural scenes is remarkably efficient. Journal of Vision, 8(6), 1103–1103.

    Google Scholar 

  • Wolfe, J. M., Horowitz, T. S., Palmer, E. M., Michod, K. O., & Van Wert, M. J. (2010a). Getting in to guided search. In V. Coltheart (Ed.), Tutorials in visual cognition. (pp. 93–120). Hove: Psychology.

    Google Scholar 

  • Wolfe, J. M., Palmer, E. M., & Horowitz, T. S. (2010b). Reaction time distributions constrain models of visual search. Vision Research, 50(14), 1304–1311.

    Google Scholar 

  • Wolfe, J. M., Birdwell, R. L., & Evans, K. K. (2011a). If you Don’t Find it Often, You Often Don’t Find It: Disease Prevalence is a Source of Miss Errors in Screening Mammography. Paper presented at the Anuual Radiological Society of North America meeting: Chicago, IL., Nov 30, 2011.

    Google Scholar 

  • Wolfe, J. M., Vo, M. L.-H., Evans, K. K., & Greene, M. R. (2011b). Visual search in scenes involves selective and non-selective pathways. Trends in Cognitive Sciences, 15(2), 77–84.

    Google Scholar 

  • Yantis, S., & Jonides, J. (1996). Attentional capture by abrupt onsets: New perceptual objects or visual masking. Journal of Experimental Psychology: Human Perception and Performance, 22(6), 1505–1513.

    PubMed  Google Scholar 

  • Yeari, M., & Goldsmith, M. (2010). Is object-based attention mandatory? Strategic control over mode of attention. Journal of Experimental Psychology: Human Perception and Performance, 36(3), 565–579.

    PubMed  Google Scholar 

  • Zohary, E., & Hochstein, S. (1989). How serial is serial processing in vision? Perception, 18, 191–200.

    PubMed  Google Scholar 

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Acknowledgements

This research was supported by grants from the National Institutes of Health and National Eye Institute (EY017001), the Office of Naval Research (ONR MURI N000141010278) and from the United States Department of Homeland Security (02-G-010).

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  1. Harvard Medical School and Brigham & Women’s Hospital, 02115, Boston, MA, USA

    Jeremy M. Wolfe

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  1. University of Nebraska, 222 Burnett Hall, Lincoln, 68588, Nebraska, USA

    Michael D. Dodd

  2. University of Nebraska, Burnett Hall 219, Lincoln, 68588-0308, Nebraska, USA

    John H. Flowers

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Wolfe, J. (2012). When do I Quit? The Search Termination Problem in Visual Search. In: Dodd, M., Flowers, J. (eds) The Influence of Attention, Learning, and Motivation on Visual Search. Nebraska Symposium on Motivation. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-4794-8_8

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