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Treffer: Frequency-based heuristics for material perception.

Title:
Frequency-based heuristics for material perception.
Authors:
Giesel M; Graduate Center for Vision Research, SUNY College of Optometry, New York, NY, USA., Zaidi Q
Source:
Journal of vision [J Vis] 2013 Dec 06; Vol. 13 (14). Date of Electronic Publication: 2013 Dec 06.
Publication Type:
Journal Article; Research Support, N.I.H., Extramural; Research Support, Non-U.S. Gov't
Language:
English
Journal Info:
Publisher: Association for Research in Vision and Ophthalmology (ARVO) Country of Publication: United States NLM ID: 101147197 Publication Model: Electronic Cited Medium: Internet ISSN: 1534-7362 (Electronic) Linking ISSN: 15347362 NLM ISO Abbreviation: J Vis Subsets: MEDLINE
Imprint Name(s):
Publication: <2002->: [Rockville, MD] : Association for Research in Vision and Ophthalmology (ARVO)
Original Publication: Charlottesville, VA : Scholar One, Inc., [2001]-
MeSH Terms:
Depth Perception/*physiology , Form Perception/*physiology, Algorithms ; Artificial Intelligence ; Contrast Sensitivity ; Cues ; Female ; Humans ; Lighting ; Male ; Pattern Recognition, Visual
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Grant Information:
R01 EY007556 United States EY NEI NIH HHS; R01 EY013312 United States EY NEI NIH HHS; EY07556 United States EY NEI NIH HHS; EY13312 United States EY NEI NIH HHS
Contributed Indexing:
Keywords: adaptation; image statistics; material perception; spatial frequency
Entry Date(s):
Date Created: 20131210 Date Completed: 20140403 Latest Revision: 20211021
Update Code:
20250114
PubMed Central ID:
PMC4523161
DOI:
10.1167/13.14.7
PMID:
24317425
Database:
MEDLINE

Weitere Informationen

People often make rapid visual judgments of the properties of surfaces they are going to walk on or touch. How do they do this when the interactions of illumination geometry with 3-D material structure and object shape result in images that inverse optics algorithms cannot resolve without externally imposed constraints? A possibly effective strategy would be to use heuristics based on information that can be gleaned rapidly from retinal images. By using perceptual scaling of a large sample of images, combined with correspondence and canonical correlation analyses, we discovered that material properties, such as roughness, thickness, and undulations, are characterized by specific scales of luminance variations. Using movies, we demonstrate that observers' percepts of these 3-D qualities vary continuously as a function of the relative energy in corresponding 2-D frequency bands. In addition, we show that judgments of roughness, thickness, and undulations are predictably altered by adaptation to dynamic noise at the corresponding scales. These results establish that the scale of local 3-D structure is critical in perceiving material properties, and that relative contrast at particular spatial frequencies is important for perceiving the critical 3-D structure from shading cues, so that cortical mechanisms for estimating material properties could be constructed by combining the parallel outputs of sets of frequency-selective neurons. These results also provide methods for remote sensing of material properties in machine vision, and rapid synthesis, editing and transfer of material properties for computer graphics and animation.