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Cited by 115

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Identification of spatially quantised tachistoscopic images of faces: How many pixels does it take to carry identity?

Bachmann, Talis·1991·European Journal of Cognitive Psychology
DOI 10.1080/09541449108406221
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Abstract

Six images of human faces were quantised into isoluminant square-shaped pixels (16 grey levels) at eight different spatial levels of quantisation. The subjects had to identify the faces that were presented with different exposure durations (from 1 to 200 msec) and with one of two brightness conditions (variable brightness in Experiment 1 or isobrightness in Experiment 2). All finer quantisation levels led to better identification than the most coarse quantisation level (15 pixels per face in the horizontal dimension) at all exposure durations. The observation of an abrupt decrease in identification efficiency on moving from 18 or more pixels per face to 15 pixels per face and the approximate equality in identification efficiency within a broad range of quantisation levels above 18 pixels per face pose some problems for existing theories of face recognition. The implications of these findings for prototype-related, auto correlation and micro genetic accounts of face and pattern processing are discussed.

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  • A minimum horizontal pixel count of 10-16 per face for a known face and 20 pixels for an unknown face is considered the bare minimum for successful identification in frontal view.

    “A minimum horizontal pixel count of 10–16 per face for a known face [121,123,124] and 20 pixels for an unknown face [92] is considered the bare minimum for successful identification in frontal view.”

    From Forensic Facial Comparison: Current Status, Limitations, and Future Directions (2021) · cites this paper as [121]

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Research works printed but not linked: 17

  1. 10.1007/BF00308675 · DOI
  2. 10.1016/0001-6918(89)90056-5 · DOI
  3. Bachmann, T. and Kahusk, N. 1987.Non monotonic micro genetic function for the perceptual representation of quantized visual images of objects. Workshop on Knowledge Representation and Information Processing. 1987, Berlin. pp.45 (Abstract)
  4. Bruce V., 1988, Recognising faces
  5. Guberman S. A., 1984, Systems research: Methodological problems 1, a yearbook 1984
  6. Gubler E. V., 1978, Computational methods of analysis and recognition of the pathological processes [in Russian]
  7. 10.1126/science.180.4091.1194 · DOI
  8. Kalmus M., 1980, Acta et Commnntationes Universitatis Tartuensic, 529, 135
  9. 10.1126/science.7394534 · DOI
  10. 10.1038/305226a0 · DOI
  11. 10.1016/0010-0285(77)90012-3 · DOI · Paper page
  12. Sergent J., 1986, Aspects of face processing
  13. Thorn R., 1975, Structural stabile and morphogenesis: An outline of a general theory of models
  14. Uttal W. R., 1975, An autocorrelation theory of form detection
  15. Uttal W. R., 1988, On seeing forms
  16. Valentine, T. 1988.A prototype model of face recognition. Paper presented at the meeting of the European Society for Cognitive Psychology. September1988, Cambridge.
  17. Watt R., 1988, Visual processing: Computational, psychophysical and cognitive research

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Metadata

Authors
Bachmann, T.
Venue
European Journal of Cognitive Psychology
Publisher
Informa UK Limited
Published
1991-01
Volume
3
Issue
1
Pages
87-103
ISSN
  • 0954-1446
  • 1464-0635
DOI
10.1080/09541449108406221
Cited by
115
References
0
Language
en

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