Document Detail

Seeing liquids from visual motion.
MedLine Citation:
PMID:  25102388     Owner:  NLM     Status:  Publisher    
Most research on human visual recognition focuses on solid objects, whose identity is defined primarily by shape. In daily life, however, we often encounter materials that have no specific form, including liquids whose shape changes dynamically over time. Here we show that human observers can recognize liquids and their viscosities solely from image motion information. Using a two-dimensional array of noise patches, we presented observers with motion vector fields derived from diverse computer rendered scenes of liquid flow. Our observers perceived liquid-like materials in the noise-based motion fields, and could judge the simulated viscosity with surprising accuracy, given total absence of non-motion information including form. We find that the critical feature for apparent liquid viscosity is local motion speed, whereas for the impression of liquidness, image statistics related to spatial smoothness - including the mean discrete Laplacian of motion vectors - is important. Our results show the brain exploits a wide range of motion statistics to identify non-solid materials.
Takahiro Kawabe; Kazushi Maruya; Roland W Fleming; Shin'ya Nishida
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Publication Detail:
Type:  JOURNAL ARTICLE     Date:  2014-8-4
Journal Detail:
Title:  Vision research     Volume:  -     ISSN:  1878-5646     ISO Abbreviation:  Vision Res.     Publication Date:  2014 Aug 
Date Detail:
Created Date:  2014-8-7     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  0417402     Medline TA:  Vision Res     Country:  -    
Other Details:
Languages:  ENG     Pagination:  -     Citation Subset:  -    
Copyright Information:
Copyright © 2014 The Authors. Published by Elsevier Ltd.. All rights reserved.
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