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Texture and haptic cues in slant discrimination: Reliability-based cue weighting without statistically optimal cue combination

2005

Article

ei


A number of models of depth cue combination suggest that the final depth percept results from a weighted average of independent depth estimates based on the different cues available. The weight of each cue in such an average is thought to depend on the reliability of each cue. In principle, such a depth estimation could be statistically optimal in the sense of producing the minimum variance unbiased estimator that can be constructed from the available information. Here we test such models using visual and haptic depth information. Different texture types produce differences in slant discrimination performance, providing a means for testing a reliability-sensitive cue combination model using texture as one of the cues to slant. Our results show that the weights for the cues were generally sensitive to their reliability, but fell short of statistically optimal combination—we find reliability-based re-weighting, but not statistically optimal cue combination.

Author(s): Rosas, P. and Wagemans, J. and Ernst, MO. and Wichmann, FA.
Journal: Journal of the Optical Society of America A
Volume: 22
Number (issue): 5
Pages: 801-809
Year: 2005
Month: May
Day: 0

Department(s): Empirical Inference
Bibtex Type: Article (article)

Digital: 0
Language: en
Organization: Max-Planck-Gesellschaft
School: Biologische Kybernetik

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BibTex

@article{2785,
  title = {Texture and haptic cues in slant discrimination: Reliability-based cue weighting without statistically optimal cue combination},
  author = {Rosas, P. and Wagemans, J. and Ernst, MO. and Wichmann, FA.},
  journal = {Journal of the Optical Society of America A},
  volume = {22},
  number = {5},
  pages = {801-809},
  organization = {Max-Planck-Gesellschaft},
  school = {Biologische Kybernetik},
  month = may,
  year = {2005},
  month_numeric = {5}
}