M
Martin S. Banks
Researcher at University of California, Berkeley
Publications - 243
Citations - 18447
Martin S. Banks is an academic researcher from University of California, Berkeley. The author has contributed to research in topics: Stereoscopy & Depth perception. The author has an hindex of 62, co-authored 234 publications receiving 16993 citations. Previous affiliations of Martin S. Banks include University of Sussex & University of Minnesota.
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Humans integrate visual and haptic information in a statistically optimal fashion.
TL;DR: The nervous system seems to combine visual and haptic information in a fashion that is similar to a maximum-likelihood integrator, and this model behaved very similarly to humans in a visual–haptic task.
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Vergence-accommodation conflicts hinder visual performance and cause visual fatigue.
TL;DR: This display is used to evaluate the influence of focus cues on perceptual distortions, fusion failures, and fatigue and shows that when focus cues are correct or nearly correct, the time required to identify a stereoscopic stimulus is reduced, stereoacuity in a time-limited task is increased, and distortions in perceived depth are reduced.
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The zone of comfort: Predicting visual discomfort with stereo displays
TL;DR: This work focused on how vergence-accommodation conflicts in stereo displays affect visual discomfort and fatigue, and found that negative conflicts are less comfortable at far distances and that positive conflicts are more comfortable at near distances.
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Combining Sensory Information: Mandatory Fusion Within, but Not Between, Senses
TL;DR: It is reported that single-cue information is indeed lost when cues from within the same sensory modality (disparity and texture gradients in vision) are combined, but not when different modalities (vision and haptics) are Combined.
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Slant from texture and disparity cues: optimal cue combination.
TL;DR: There is a growing empirical consensus that MLE provides a good quantitative account of cue combination and that sensory information is used in a manner that maximizes the precision of perceptual estimates.