Literature DB >> 10748939

Experience-dependent integration of texture and motion cues to depth.

R A Jacobs1, I Fine.   

Abstract

Previous investigators have shown that observers' visual cue combination strategies are remarkably flexible in the sense that these strategies adapt on the basis of the estimated reliabilities of the visual cues. However, these researchers have not addressed how observers' acquire these estimated reliabilities. This article studies observers' abilities to learn cue combination strategies. Subjects made depth judgments about simulated cylinders whose shapes were indicated by motion and texture cues. Because the two cues could indicate different shapes, it was possible to design tasks in which one cue provided useful information for making depth judgments, whereas the other cue was irrelevant. The results of experiment 1 suggest that observers' cue combination strategies are adaptable as a function of training; subjects adjusted their cue combination rules to use a cue more heavily when the cue was informative on a task versus when the cue was irrelevant. Experiment 2 demonstrated that experience-dependent adaptation of cue combination rules is context-sensitive. On trials with presentations of short cylinders, one cue was informative, whereas on trials with presentations of tall cylinders, the other cue was informative. The results suggest that observers can learn multiple cue combination rules, and can learn to apply each rule in the appropriate context. Experiment 3 demonstrated a possible limitation on the context-sensitivity of adaptation of cue combination rules. One cue was informative on trials with presentations of cylinders at a left oblique orientation, whereas the other cue was informative on trials with presentations of cylinders at a right oblique orientation. The results indicate that observers did not learn to use different cue combination rules in different contexts under these circumstances. These results are consistent with the hypothesis that observers' visual systems are biased to learn to perceive in the same way views of bilaterally symmetric objects that differ solely by a symmetry transformation. Taken in conjunction with the results of Experiment 2, this means that the visual learning mechanism underlying cue combination adaptation is biased such that some sets of statistics are more easily learned than others.

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Mesh:

Year:  1999        PMID: 10748939     DOI: 10.1016/s0042-6989(99)00120-0

Source DB:  PubMed          Journal:  Vision Res        ISSN: 0042-6989            Impact factor:   1.886


  21 in total

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Journal:  J Vis       Date:  2006-05-05       Impact factor: 2.240

3.  The effect of viewpoint on perceived visual roughness.

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4.  A neural model for the integration of stereopsis and motion parallax in structure-from-motion.

Authors:  Julian Martin Fernandez; Bart Farell
Journal:  Neurocomputing       Date:  2008-03       Impact factor: 5.719

5.  The role of visuohaptic experience in visually perceived depth.

Authors:  Yun-Xian Ho; Sascha Serwe; Julia Trommershäuser; Laurence T Maloney; Michael S Landy
Journal:  J Neurophysiol       Date:  2009-04-08       Impact factor: 2.714

6.  How much to trust the senses: likelihood learning.

Authors:  Yoshiyuki Sato; Konrad P Kording
Journal:  J Vis       Date:  2014-11-14       Impact factor: 2.240

7.  Probabilistic Representation in Human Visual Cortex Reflects Uncertainty in Serial Decisions.

Authors:  Ruben S van Bergen; Janneke F M Jehee
Journal:  J Neurosci       Date:  2019-09-03       Impact factor: 6.167

8.  Influence of prior and visual information on eye movements in amblyopic children.

Authors:  Coralie Hemptinne; Nicolas Deravet; Jean-Jacques Orban de Xivry; Philippe Lefèvre; Demet Yüksel
Journal:  J Comput Neurosci       Date:  2020-09-08       Impact factor: 1.621

9.  Experience affects the use of ego-motion signals during 3D shape perception.

Authors:  Anshul Jain; Benjamin T Backus
Journal:  J Vis       Date:  2010-12-29       Impact factor: 2.240

10.  Using the past to estimate sensory uncertainty.

Authors:  Ulrik Beierholm; Tim Rohe; Ambra Ferrari; Oliver Stegle; Uta Noppeney
Journal:  Elife       Date:  2020-12-15       Impact factor: 8.140

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