ArticleCurrent biology : CB2018
Visual Features in the Perception of Liquids.
Article in Current biology : CB, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.
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Who cites it
32 citing papers in PubMed.
- Material discrimination relies on context-dependent active sensing strategies.Journal of vision · 2026Article
- Perceiving material qualities from moving contours.Scientific reports · 2026Article
- The visual perception of relative mass from object collisions.Journal of vision · 2026Article
- The identification of materials from patterns of fluid flow.Journal of vision · 2025Article
- Computational models reveal that intuitive physics underlies visual processing of soft objects.Nature communications · 2025Article
- Optical material properties affect detection of deformation of non-rigid rotating objects, but only slightly.Journal of vision · 2025Article
- Expanding the V1-MT model to the estimation of perceived fluid direction.Scientific reports · 2025Article
- Core dimensions of human material perception.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Both optical and rheological properties contribute to viscosity judgements when comparing real liquids using vision and touch.Royal Society open science · 2025Article
- Perception of nonrigid structures from motion using tracking image gradient vectors.Frontiers in psychology · 2025Article
- Probing the link between vision and language in material perception using psychophysics and unsupervised learning.PLoS computational biology · 2024Article
- Probing the Link Between Vision and Language in Material Perception Using Psychophysics and Unsupervised Learning.bioRxiv : the preprint server for biology · 2024Article
- Perceptual dimensions of wood materials.Journal of vision · 2024Article
- Perception of 3D shape integrates intuitive physics and analysis-by-synthesis.Nature human behaviour · 2024Article
- A dedicated mental resource for intuitive physics.iScience · 2024Article
- Go with the flow: deep learning methods for autonomous viscosity estimations.Digital discovery · 2023Article
- EEG Decoding Reveals Neural Predictions for Naturalistic Material Behaviors.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2023Article
- Material category of visual objects computed from specular image structure.Nature human behaviour · 2023Article
- Assessing the representational structure of softness activated by words.Scientific reports · 2023Article
- Unsupervised learning reveals interpretable latent representations for translucency perception.PLoS computational biology · 2023Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Perceptual constancy-identifying surfaces and objects across large image changes-remains an important challenge for visual neuroscience [1-8]. Liquids are particularly challenging because they respond to external forces in complex, highly variable ways, presenting an enormous range of images to the visual system. To achieve constancy, the brain must perform a causal inference [9-11] that disentangles the liquid's viscosity from external factors-like gravity and object interactions-that also affect the liquid's behavior. Here, we tested whether the visual system estimates viscosity using "midlevel" features [12-14] that respond more to viscosity than other factors. Observers reported the perceived viscosity of simulated liquids ranging from water to molten glass exhibiting diverse behaviors (e.g., pouring, stirring). A separate group of observers rated the same animations for 20 midlevel 3D shape and motion features. Applying factor analysis to the feature ratings reveals that a weighted combination of four underlying factors (distribution, irregularity, rectilinearity, and dynamics) predicted perceived viscosity very well across this wide range of contexts (R
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