Cited by 281Visual perception and processing mechanismsVisual Attention and Saliency DetectionFace Recognition and Perception

Perception of Objects in Natural Scenes: Is It Really Attention Free?

Evans, Karla K., Treisman, Anne·2005·Journal of Experimental Psychology: Human Perception and Performance

Abstract

Studies have suggested attention-free semantic processing of natural scenes in which concurrent tasks leave category detection unimpaired (e.g., F. Li, R. VanRullen, C. Koch, & P. Perona, 2002). Could this ability reflect detection of disjunctive feature sets rather than high-level binding? Participants detected an animal target in a rapid serial visual presentation (RSVP) sequence and then reported its identity and location. They frequently failed to identify or to localize targets that they had correctly detected, suggesting that detection was based only on partial processing. Detection of targets was considerably worse in sequences that also contained humans, presumably because of shared features. When 2 targets were presented in RSVP, a prolonged attentional blink appeared that was almost eliminated when both targets were detected without being identified. The results suggest rapid feature analysis mediating detection, followed by attention-demanding binding for identification and localization.

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Crossref · 10.1037/0096-1523.31.6.1476

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  • Key to the recognition performance of the model is the large number of tuned units across its hierarchical architecture, which is a direct consequence of learning from natural images and represents a redundant dictionary of fragment-like features that span a range of selectivities and invariances.

    “Key to the recognition performance of the model is the large number of tuned units across its hierarchical architecture, which is a direct consequence of the learning from natural images and represent a redundant dictionary of fragment-like features (12, 17, 41) that span a range of selectivities and invariances.”

    From A feedforward architecture accounts for rapid categorization (2007) · cites this paper as [41]

  • Our results agree with several theories of visual processing that suggest that an initial feedforward sweep driven by bottom-up inputs builds a base representation that relies on a basic dictionary of generic features before more complex tasks or visual routines can take place through recurrent projections from higher areas.

    “Our results indeed agree with several theories of visual processing that suggest that an initial feedforward sweep driven by bottom-up inputs builds a base representation that relies on a basic dictionary of generic features (11-13, 17, 41) before more complex tasks or visual routines can take place through recurrent projections from higher areas (20, 42, 43, 45).”

    From A feedforward architecture accounts for rapid categorization (2007) · cites this paper as [41]

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Authors
Evans, K. K., & Treisman, A.
Affiliations
Princeton University (US)
Venue
Journal of Experimental Psychology: Human Perception and Performance
Published
2005
Volume
31
Issue
6
Pages
1476-1492
ISSN
  • 0096-1523 (ISSN-L)
  • 1939-1277
OpenAlex
W2130250402
Cited by
281
References
74
Citations by year
2026: 3 · 2025: 7 · 2024: 3 · 2023: 4 · 2022: 10 · 2021: 12 · 2020: 23 · 2019: 15 · 2018: 15 · 2017: 9 · 2016: 18 · 2015: 15 · 2014: 19 · 2013: 17 · 2012: 18
FWCI
7.09
Type
journal article
Language
en
Open access
closed
Locations
  • Journal of Experimental Psychology Human Perception & Performance (publishedVersion)
  • PubMed (publishedVersion)
Funders
  • National Institutes of Health (5r01mh058383-07)
  • National Institute of Mental Health (P50 MH62196, 2R01 MH 058383-04A1, P50MH062196)
Topics
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Visual perception and processing mechanisms
  • Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Visual Attention and Saliency Detection
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Face Recognition and Perception
Keywords
natural scene perception, attentional blink, rapid serial visual presentation, object detection, object identification, object localization, feature binding, shared features
MeSH terms
Adolescent, Adult, Attention, Environment, Female, Humans, Male, Semantics, Visual Perception

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