Search results for '*Visual Search' (try it on Scholar)

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  1. Emily Wiecek, Louis R. Pasquale, Jozsef Fiser, Steven Dakin & Peter J. Bex (2012). Effects of Peripheral Visual Field Loss on Eye Movements During Visual Search. Frontiers in Psychology 3.score: 240.0
    Natural vision involves sequential eye movements that bring the fovea to locations selected by peripheral vision. How peripheral visual field loss (PVFL) affects this process is not well understood. We examine how the location and extent of PVFL affects eye movement behavior in a naturalistic visual search task. Ten patients with PVFL and thirteen normally sighted subjects with full visual fields (FVF) completed 30 visual searches monocularly. Subjects located a 4 x 4 degree target, pseudo-randomly selected within a 26 (...)
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  2. Peter J. Bex Emily Wiecek, Louis R. Pasquale, Jozsef Fiser, Steven Dakin (2012). Effects of Peripheral Visual Field Loss on Eye Movements During Visual Search. Frontiers in Psychology 3.score: 240.0
    Natural vision involves sequential eye movements that bring the fovea to locations selected by peripheral vision. How peripheral visual field loss (PVFL) affects this process is not well understood. We examine how the location and extent of PVFL affects eye movement behavior in a naturalistic visual search task. Ten patients with PVFL and thirteen normally sighted subjects with full visual fields (FVF) completed 30 visual searches monocularly. Subjects located a 4 x 4 degree target, pseudo-randomly selected within a 26 (...)
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  3. F. Geringswald, F. Baumgartner & S. Pollmann (2011). Simulated Loss of Foveal Vision Eliminates Visual Search Advantage in Repeated Displays. Frontiers in Human Neuroscience 6:134-134.score: 240.0
    In the contextual cueing paradigm, incidental visual learning of repeated distractor configurations leads to faster search times in repeated compared to new displays. This contextual cueing is closely linked to the visual exploration of the search arrays as indicated by fewer fixations and more efficient scan paths in repeated search arrays. Here, we examined contextual cueing under impaired visual exploration induced by a simulated central scotoma that causes the participant to rely on extrafoveal vision. We let normal-sighted (...)
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  4. Andreas Kotowicz, Ueli Rutishauser & Christof Koch (2010). Time Course of Target Recognition in Visual Search. Frontiers in Human Neuroscience 4.score: 240.0
    Visual search is a ubiquitous task of great importance: it allows us to quickly find the objects that we are looking for. During active search for an object (target), eye movements are made to different parts of the scene. Fixation locations are chosen based on a combination of information about the target and the visual input. At the end of a successful search, the eyes typically fixate on the target. But does this imply that target identification occurs (...)
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  5. Julia Fellrath, Vanessa Blanche-Durbec, Armin Schnider, Anne-Sophie Jacquemoud & Radek Ptak (2012). Visual Search in Spatial Neglect Studied with a Preview Paradigm. Frontiers in Human Neuroscience 6:93-93.score: 240.0
    Impaired visual search is a hallmark of spatial neglect. When searching for a unique feature (e.g., colour) neglect patients often show only slight visual field asymmetries. In contrast, when the target is defined by a combination of features (e.g., colour and form) they exhibit a severe deficit of contralesional search. This finding suggests a selective impairment of the serial deployment of spatial attention. Here, we examined this deficit with a preview paradigm. Neglect patients searched for a target defined (...)
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  6. Hermann J. Müller Joseph Krummenacher (2012). Dynamic Weighting of Feature Dimensions in Visual Search: Behavioral and Psychophysiological Evidence. Frontiers in Psychology 3.score: 240.0
    The notion that the neural activations representing a limited set of visual features in the brain are modulated by a process prioritizing a circumscribed part of the visual field has turned out to be a powerful account of selective attention. Extensions of the original approach assuming the existence of feature-based saliency signals governing the allocation of focal attention have recently evolved to explain the spatial and temporal dynamics of the relative strengths of feature-based saliency representations. Here we review recent behavioral (...)
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  7. S. Stigchel, R. A. Bethlehem, B. P. Klein, T. T. Berendschot, T. C. Nijboer & S. O. Dumoulin (2012). Macular Degeneration Affects Eye Movement Behavior During Visual Search. Frontiers in Psychology 4:579-579.score: 240.0
    Patients with a scotoma in their central vision (e.g. due to macular degeneration, MD) commonly adopt a strategy to direct the eyes such that the image falls onto a peripheral location on the retina. This location is referred to as the preferred retinal locus (PRL). Although previous research has investigated the characteristics of this PRL, it is unclear whether eye movement metrics are modulated by peripheral viewing with a PRL as measured during a visual search paradigm. To this end, (...)
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  8. Bryan Cort & Britt Anderson (2013). Conditional Probability Modulates Visual Search Efficiency. Frontiers in Human Neuroscience 7.score: 240.0
    We investigated the effects of probability on visual search. Previous work has shown that people can utilize spatial and sequential probability information to improve target detection. We hypothesized that performance improvements from probability information would extend to the efficiency of visual search. Our task was a simple visual search in which the target was always present among a field of distractors, and could take one of two colors. The absolute probability of the target being either color was (...)
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  9. Hermann J. Müller Markus Conci, Martina Zellin (2012). Whatever After Next? Adaptive Predictions Based on Short- and Long-Term Memory in Visual Search. Frontiers in Psychology 3.score: 240.0
    Whatever after Next? Adaptive Predictions Based on Short- and Long-Term Memory in Visual Search.
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  10. Michael G. Coles (1972). Cardiac and Respiratory Activity During Visual Search. Journal of Experimental Psychology 96 (2):371.score: 210.0
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  11. Joseph F. Hearns & Stanley M. Moss (1968). Effect of Method of Payoff on the Detection of Targets in a Visual Search Task. Journal of Experimental Psychology 78 (4p1):569.score: 210.0
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  12. Charles R. Snyder (1972). Selection, Inspection, and Naming in Visual Search. Journal of Experimental Psychology 92 (3):428.score: 210.0
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  13. A. Carpenter (1948). The Rate of Blinking During Prolonged Visual Search. Journal of Experimental Psychology 38 (5):587.score: 210.0
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  14. Harriet Foster (1962). The Operation of Set in a Visual Search Task. Journal of Experimental Psychology 63 (1):74.score: 210.0
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  15. Ryoichi Nakashima, Kazufumi Kobayashi, Eriko Maeda, Takeharu Yoshikawa & Kazuhiko Yokosawa (2013). Visual Search of Experts in Medical Image Reading: The Effect of Training, Target Prevalence, and Expert Knowledge. Frontiers in Psychology 4.score: 210.0
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  16. Gerald J. Organt (1971). Effect of M Value on Visual Search. Journal of Experimental Psychology 89 (1):171.score: 210.0
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  17. Marc Pomplun, Eyal M. Reingold & Jiye Shen (2003). Area Activation: A Computational Model of Saccadic Selectivity in Visual Search. Cognitive Science 27 (2):299-312.score: 210.0
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  18. Jane M. Connor (1972). Serial and Parallel Encoding Processes in Memory and Visual Search. Journal of Experimental Psychology 96 (2):363.score: 210.0
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  19. Ian E. Gordon, Victor Dulewicz & Meg Winwood (1971). Irrelevant Item Variety and Visual Search. Journal of Experimental Psychology 88 (2):295.score: 210.0
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  20. John D. Gould & David R. Peeples (1970). Eye Movements During Visual Search and Discrimination of Meaningless, Symbol, and Object Patterns. Journal of Experimental Psychology 85 (1):51.score: 210.0
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  21. Bert F. Green & Lois K. Anderson (1956). Color Coding in a Visual Search Task. Journal of Experimental Psychology 51 (1):19.score: 210.0
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  22. Joseph F. Hearns (1973). Effects of Prestimulus Cuing and Target Load Variability on Maintenance of Response Strategies in a Visual Search Task. Journal of Experimental Psychology 99 (3):375-380.score: 210.0
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  23. Ira T. Kaplan, Thomas Carvellas & William Metlay (1966). Visual Search and Immediate Memory. Journal of Experimental Psychology 71 (4):488.score: 210.0
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  24. Lester E. Krueger (1970). Effect of Frequency of Display on Speed of Visual Search. Journal of Experimental Psychology 84 (3):495.score: 210.0
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  25. M. Lallier, S. Donnadieu & S. Valdois (2012). Investigating the Role of Visual and Auditory Search in Reading and Developmental Dyslexia. Frontiers in Human Neuroscience 7:597-597.score: 210.0
    It has been suggested that auditory and visual sequential processing deficits contribute to phonological disorders in developmental dyslexia. As an alternative explanation to a phonological deficit as the proximal cause for reading disorders, the visual attention span hypothesis (VA Span) suggests that difficulties in processing visual elements simultaneously lead to dyslexia, regardless of the presence of a phonological disorder. In this study, we assessed whether deficits in processing simultaneously displayed visual or auditory elements is linked to dyslexia associated with a (...)
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  26. William Metlay, Mark Sokoloff & Ira T. Kaplan (1970). Visual Search for Multiple Targets. Journal of Experimental Psychology 85 (1):148.score: 210.0
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  27. Sidney L. Smith (1962). Color Coding and Visual Search. Journal of Experimental Psychology 64 (5):434.score: 210.0
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  28. Yun Xu, Emily C. Higgins, Mei Xiao & Marc Pomplun (2007). Mapping the Color Space of Saccadic Selectivity in Visual Search. Cognitive Science 31 (5):877-887.score: 210.0
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  29. John D. Gould (1973). Eye Movements During Visual Search and Memory Search. Journal of Experimental Psychology 98 (1):184.score: 198.0
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  30. R. Rensink (2000). Visual Search for Change: A Probe Into the Nature of Attentional Processing. Visual Cognition 7:345-376.score: 186.0
    A set of visual search experiments tested the proposal that focused attention is needed to detect change. Displays were arrays of rectangles, with the target being the item that continually changed its orientation or contrast polarity. Five aspects of performance were examined: linearity of response, processing time, capacity, selectivity, and memory trace. Detection of change was found to be a self-terminating process requiring a time that increased linearly with the number of items in the display. Capacity for orientation was (...)
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  31. Nicoletta Orlandi (2012). Visual Switching: The Illusion of Instantaneity and Visual Search. Review of Philosophy and Psychology 3 (4):469-480.score: 180.0
    This paper questions two prima facie plausible claims concerning switching in the presence of ambiguous figures. The first is the claim that reversing is an instantaneous process. The second is the claim that the ability to reverse demonstrates the interpretive, inferential and constructive nature of visual processing. Empirical studies show that optical and cerebral events related to switching protract in time in a way that clashes with its perceived instantaneity. The studies further suggest an alternative theory of reversing: according to (...)
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  32. Ronald Rensink, The Influence of Cast Shadows on Visual Search.score: 180.0
    We show that cast shadows can have a significant influence on the speed of visual search. In particular, we find that search based on the shape of a region is affected when the region is darker than the background and corresponds to a shadow formed by lighting from above. Results support the proposal that an early-level system rapidly identifies regions as shadows and then discounts them, making their shapes more difficult to access. Several constraints used by this system (...)
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  33. Ronald Rensink, Sensitivity to Three-Dimensional Orientation in Visual Search.score: 180.0
    Previous theories of early vision have assumed that visual search is based on simple two-dimensional aspects of an image, such as the orientation of edges and lines. It is shown here that search can also be based on three-dimensional orientation of objects in the corresponding scene, provided that these objects are simple convex blocks. Direct comparison shows that image-based and scene-based orientation are similar in their ability to facilitate search. These findings support the hypothesis that scene-based properties (...)
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  34. Ronald Rensink, Rapid Resumption: A New Form of Memory in Visual Search.score: 180.0
    We report on a new visual search task in which observers make highly accurate two-alternative forced-choice responses within 100-400 ms of display onset. This is a striking result, since accurate responding in a difficult search of this kind is usually possible only after at least 500 ms from display onset. The conditions under which such rapid responses are obtained involve brief initial glimpses of a search display interrupted by either a blank screen or a glimpse of a (...)
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  35. Ronald Rensink, The Influence of Line Relations on Visual Search.score: 180.0
    It has generally been assumed that parallel visual search can only be based on the presence of simple features -- the spatial relations between features do not influence this process. We describe a series of visual search experiments that contradict this assumption. Search for line drawings of opaque polyhedra is greatly influenced by some line relations. In particular, search is rapid for line drawings (i) that have arrow- and Y-junctions corresponding to corners formed from orthogonal surfaces, (...)
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  36. Ronald Rensink, Influence of Scene-Based Properties on Visual Search.score: 180.0
    The task of visual search is to determine as rapidly as possible whether a target item is present or absent in a display. Rapidly detected items are thought to contain features that correspond to primitive elements in the human visual system. In previous theories, it has been assumed that visual search is based on simple two-dimensional features in the image. However, visual search also has access to another level of representation, one that describes properties in the corresponding (...)
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  37. Ronald Rensink, Vsearch Color: Full-Color Visual Search Experiments on the MacIntosh II.score: 180.0
    We describe an update to our visual search software for the Macintosh line of computers. The new software, VSearch Color, gives users access to the full-color capabilities of the Macintosh II line. One of the key features of the new software is its ability to treat graphics information separately from color information. This makes it easy to study color independently of form, to design experiments based on isoluminant stimuli, and to incorporate texture segregation, visual identification, number discrimination, adaptation, masking, (...)
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  38. Allison M. Waters & Ottmar V. Lipp (2008). Visual Search for Emotional Faces in Children. Cognition and Emotion 22 (7):1306-1326.score: 180.0
    The ability to rapidly detect facial expressions of anger and threat over other salient expressions has adaptive value across the lifespan. Although studies have demonstrated this threat superiority effect in adults, surprisingly little research has examined the development of this process over the childhood period. In this study, we examined the efficiency of children's facial processing in visual search tasks. In Experiment 1, children (N=49) aged 8 to 11 years were faster and more accurate in detecting angry target faces (...)
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  39. Kai J. Miller, Dora Hermes, Christopher J. Honey, Mohit Sharma, Rajesh P. N. Rao, Marcel Den Nijs, Eberhard E. Fetz, Terrence J. Sejnowski, Adam O. Hebb, Jeffrey G. Ojemann, Scott Makeig & Eric C. Leuthardt (2010). Dynamic Modulation of Local Population Activity by Rhythm Phase in Human Occipital Cortex During a Visual Search Task. Frontiers in Human Neuroscience 4:197.score: 180.0
    Brain rhythms are more than just passive phenomena in visual cortex. For the first time, we show that the physiology underlying brain rhythms actively suppresses and releases cortical areas on a second-to-second basis during visual processing. Furthermore, their influence is specific at the scale of individual gyri. We quantified the interaction between broadband spectral change and brain rhythms on a second-to-second basis in electrocorticographic (ECoG) measurement of brain surface potentials in five human subjects during a visual search task. Comparison (...)
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  40. Charles W. Eriksen & James F. Collins (1969). Visual Perceptual Rate Under Two Conditions of Search. Journal of Experimental Psychology 80 (3p1):489.score: 168.0
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  41. Lester E. Krueger (1970). Search Time in a Redundant Visual Display. Journal of Experimental Psychology 83 (3p1):391.score: 168.0
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  42. S. Viterbo McCarthy (1972). Visual Serial Search Performance for Number and Letter Targets. Journal of Experimental Psychology 95 (1):233.score: 168.0
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  43. Ian E. Gordon (1968). Interactions Between Items in Visual Search. Journal of Experimental Psychology 76 (3p1):348.score: 162.0
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  44. Donald A. Shurtleff & Marion Y. Marsetta (1968). Visual Search in a Letter-Canceling Task Reexamined. Journal of Experimental Psychology 77 (1):19-23.score: 162.0
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  45. and Anling Rao Anna C. Nobre, Ivan C. Griffin (2007). Spatial Attention Can Bias Search in Visual Short-Term Memory. Frontiers in Human Neuroscience 1.score: 156.0
    Whereas top-down attentional control is known to bias perceptual functions at many levels of stimulus analysis, its possible influence over memory-related functions remains uncharted. Our experiment combined behavioral measures and event-related potentials (ERPs) to test the ability of spatial orienting to bias functions associated with visual short-term memory (VSTM), and to shed light on the neural mechanisms involved. In particular, we investigated whether orienting attention to a spatial location within an array maintained in VSTM could facilitate the search for (...)
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  46. John Palmer (1998). Attentional Effects in Visual Search: Relating Search Accuracy and Search Time. In Richard D. Wright (ed.), Visual Attention. Oxford University Press. 8--348.score: 156.0
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  47. Diane E. Williams, Patterns of Eye Movements During Parallel and Serial Visual Search Tasks.score: 152.0
    Abstnn Eye movements were monitored while subjects performed parallel and serial sarah tasks. In Experiment la, subjects searched for an “O' among "X"s (parallel condition) and for a 'T" among "L"s (serial condition). In the parallel condition of Eqcriment lb, “q)" was the target and “O"s were distractors; in the serial condition, time..
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  48. Marvin M. Chun (2012). Perceptual Learning and Memory in Visual Search. In Jeremy M. Wolfe & Lynn C. Robertson (eds.), From Perception to Consciousness: Searching with Anne Treisman. Oxford University Press.score: 152.0
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  49. M. Marvin (2012). Perceptual Learning and Memory in Visual Search. In Jeremy M. Wolfe & Lynn C. Robertson (eds.), From Perception to Consciousness: Searching with Anne Treisman. Oxford University Press. 227.score: 152.0
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  50. R. Sireteanu, R. Rettenbach & G. Diller (1996). Texture Segmentation and Visual Search in Deaf and Hearing Subjects: Evidence for Compensation? In Enrique Villanueva (ed.), Perception. Ridgeview. 4-5.score: 150.0
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