Human efficiency for recognizing 3-D objects in luminance noise

Human efficiency for recognizing 3-D objects in luminance noise The purpose of this study was to establish how efficiently humans use visual information to recognize simple 3-D objects. The stimuli were computer-rendered images of four simple 3-D objects—wedge, cone, cylinder, and pyramid—each rendered from 8 randomly chosen viewing positions as shaded objects, line drawings, or silhouettes. The objects were presented in static, 2-D Gaussian luminance noise. The observer's task was to indicate which of the four objects had been presented. We obtained human contrast thresholds for recognition, and compared these to an ideal observer's thresholds to obtain efficiencies. In two auxiliary experiments, we measured efficiencies for object detection and letter recognition. Our results showed that human object-recognition efficiency is low (3–8%) when compared to efficiencies reported for some other visual-information processing tasks. The low efficiency means that human recognition performance is limited primarily by factors intrinsic to the observer rather than the information content of the stimuli. We found three factors that play a large role in accounting for low object-recognition efficiency: stimulus size, spatial uncertainty, and detection efficiency. Four other factors play a smaller role in limiting object-recognition efficiency: observers' internal noise, stimulus rendering condition, stimulus familiarity, and categorization across views. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Vision Research Elsevier

Human efficiency for recognizing 3-D objects in luminance noise

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Publisher
Elsevier
Copyright
Copyright © 1995 Elsevier Science Ltd
ISSN
0042-6989
eISSN
1878-5646
DOI
10.1016/0042-6989(95)00070-G
Publisher site
See Article on Publisher Site

Abstract

The purpose of this study was to establish how efficiently humans use visual information to recognize simple 3-D objects. The stimuli were computer-rendered images of four simple 3-D objects—wedge, cone, cylinder, and pyramid—each rendered from 8 randomly chosen viewing positions as shaded objects, line drawings, or silhouettes. The objects were presented in static, 2-D Gaussian luminance noise. The observer's task was to indicate which of the four objects had been presented. We obtained human contrast thresholds for recognition, and compared these to an ideal observer's thresholds to obtain efficiencies. In two auxiliary experiments, we measured efficiencies for object detection and letter recognition. Our results showed that human object-recognition efficiency is low (3–8%) when compared to efficiencies reported for some other visual-information processing tasks. The low efficiency means that human recognition performance is limited primarily by factors intrinsic to the observer rather than the information content of the stimuli. We found three factors that play a large role in accounting for low object-recognition efficiency: stimulus size, spatial uncertainty, and detection efficiency. Four other factors play a smaller role in limiting object-recognition efficiency: observers' internal noise, stimulus rendering condition, stimulus familiarity, and categorization across views.

Journal

Vision ResearchElsevier

Published: Nov 1, 1995

References

  • Human efficiency for recognizing and detecting low-pass filtered objects
    Braje, W.L.; Tjan, B.S.; Legge, G.E.
  • Object-centered encoding by face-selective neurons in the cortex in the superior temporal sulcus of the monkey
    Hasselmo, M.E.; Rolls, E.T.; Baylis, G.C.; Nalwa, V.
  • Energy, quanta, and vision
    Hecht, S.; Shlaer, S.; Pirenne, M.H.
  • Object classification for human and ideal observers
    Liu, Z.; Kersten, D.; Knill, D.C.
  • Shape information from shading: a theory about human perception
    Pentland, A.
  • Sequential estimation of points on a psychometric function
    Wetherill, G.B.; Levitt, H.

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