|Appears in Collections:||Psychology Journal Articles|
|Peer Review Status:||Refereed|
|Title:||Image statistics determine the integration of visual cues to motion-in-depth|
|Citation:||Goutcher R, Murray L & Benz B (2022) Image statistics determine the integration of visual cues to motion-in-depth. Scientific Reports, 12 (1), Art. No.: 7941. https://doi.org/10.1038/s41598-022-12051-5|
|Abstract:||Motion-in-depth perception is critical in enabling animals to avoid hazards and respond to potential threats. For humans, important visual cues for motion-in-depth include changing disparity (CD) and changing image size (CS). The interpretation and integration of these cues depends upon multiple scene parameters, such as distance moved, object size and viewing distance, posing a significant computational challenge. We show that motion-in-depth cue integration depends upon sensitivity to the joint probabilities of the scene parameters determining these signals, and on the probability of CD and CS signals co-occurring. Models that took these factors into account predicted human performance in speed-in-depth and cue conflict discrimination tasks, where standard linear integration models could not. These results suggest that cue integration is affected by both the uncertainty of sensory signals and the mapping of those signals to real-world properties. Evidence of a role for such mappings demonstrates the importance of scene and image statistics to the processes underpinning cue integration and the perception of motion-in-depth.|
|Rights:||This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.|
|Goutcher_et_al-2022-Scientific_Reports.pdf||Fulltext - Published Version||1.58 MB||Adobe PDF||View/Open|
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