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Rethinking the roles of selective attention and economical encoding in vision
Rosenholtz, Ruth; Black, Michael (2013)
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mla
clipboard		 Rosenholtz R., et al. "Rethinking the roles of selective attention and economical encoding in vision.", timms video, Universität Tübingen (2013): https://timms.uni-tuebingen.de:443/tp/UT_20130926_005_bestcon_0001. Accessed 09 Mar 2025.
apa
clipboard		 Rosenholtz, R. & Black, M. (2013). Rethinking the roles of selective attention and economical encoding in vision. timms video: Universität Tübingen. Retrieved March 09, 2025 from the World Wide Web https://timms.uni-tuebingen.de:443/tp/UT_20130926_005_bestcon_0001
harvard
clipboard		 Rosenholtz, R. and Black, M. (2013). Rethinking the roles of selective attention and economical encoding in vision [Online video]. 26 September. Available at: https://timms.uni-tuebingen.de:443/tp/UT_20130926_005_bestcon_0001 (Accessed: 9 March 2025).
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title: Rethinking the roles of selective attention and economical encoding in vision
alt. title: Bernstein Conference 2013: Computational Vision
creators: Rosenholtz, Ruth (author), Black, Michael (annotator)
subjects: Bernstein Conference, Computational Neuroscience, Computational Vision, Selective Attention, Economical Encoding, Vision, Ruth Rosenholtz
description: Bernstein Conference 2013, 24. bis 27. September 2013
abstract: Considerable research points to a bottleneck in visual processing. According to the traditional view, at any given moment selective attention allows only a small portion of the visual input to get through the bottleneck for further processing. Some processing can occur "preattentively" and guide this selection. Much of the early research on visual search aimed at determining what processing could occur preattentively, and what required selective attention. While this view of visual processing has held sway for many years, it has also been problematic. My lab proposes an alternative, in which the visual system’s strategy for dealing with limited capacity focuses on compression of the visual input, rather than on selective attention. I will demonstrate that this model can predict not only classic results in visual search, but also phenomena that were problematic for the traditional selective attention story.
publisher: ZDV Universität Tübingen
contributors: Bernstein Center for Computational Neuroscience Tübingen (BCCN) (producer), Bethge, Matthias (organizer), Wichmann, Felix (organizer), Lam, Judith (organizer), Macke, Jakob (organizer)
creation date: 2013-09-26
dc type: image
localtype: video
identifier: UT_20130926_005_bestcon_0001
language: eng
rights: Url: https://timmsstatic.uni-tuebingen.de/jtimms/TimmsDisclaimer.html?638770882644254125