@poster{2532,
  title = {Texture and Haptic Cues in Slant Discrimination: Measuring the Effect of Texture Type},
  abstract = {In a number of models of depth cue combination the depth percept is constructed via a weighted
  average combination of independent depth estimations. The inuence of each cue in such average
  depends on the reliability of the source of information [1,5]. In particular, Ernst and Banks
  (2002) formulate such combination as that of the minimum variance unbiased estimator that
  can be constructed from the available cues. We have observed systematic differences in slant
  discrimination performance of human observers when different types of textures were used as
  cue to slant [4]. If the depth percept behaves as described above, our measurements of the
  slopes of the psychometric functions provide the predicted weights for the texture cue for the
  ranked texture types. However, the results for slant discrimination obtained when combining
  these texture types with object motion results are difcult to reconcile with the minimum variance
  unbiased estimator model [3]. This apparent failure of such model might be explained by
  the existence of a coupling of texture and motion, violating the assumption of independence of
  cues. Hillis, Ernst, Banks, and Landy (2002) [2] have shown that while for between-modality
  combination the human visual system has access to the single-cue information, for withinmodality
  combination (visual cues) the single-cue information is lost. This suggests a coupling
  between visual cues and independence between visual and haptic cues. Then, in the present
  study we combined the different texture types with haptic information in a slant discrimination
  task, to test whether in the between-modality condition these cues are combined as predicted
  by an unbiased, minimum variance estimator model. The measured weights for the cues were
  consistent with a combination rule sensitive to the reliability of the sources of information, but
  did not match the predictions of a statistically optimal combination.},
  volume = {7},
  pages = {165},
  editors = {B{\"u}lthoff, H. H., H. A. Mallot, R. Ulrich, F. A. Wichmann},
  organization = {Max-Planck-Gesellschaft},
  school = {Biologische Kybernetik},
  month = feb,
  year = {2004},
  slug = {2532},
  author = {Rosas, P. and Wichmann, FA. and Ernst, MO. and Wagemans, J.},
  month_numeric = {2}
}