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Poster

Manifesto for the Study of Material Perception

MPG-Autoren
http://pubman.mpdl.mpg.de/cone/persons/resource/persons83913

Fleming,  RW
Research Group Computational Vision and Neuroscience, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Zitation

Fleming, R. (2006). Manifesto for the Study of Material Perception. Poster presented at 9th Tübingen Perception Conference (TWK 2006), Tübingen, Germany.


Zitierlink: http://hdl.handle.net/11858/00-001M-0000-0013-D2A7-F
Zusammenfassung
When we look at everyday things, we not only perceive their 3D shape and identity, but also we generally enjoy a distinct visual impression of their material properties. Without touching an object, we can usually tell at a glance whether it is soggy or dry, soft or hard, smooth or rough. How does the visual system recognize materials? What are the major challenges that the visual system faces? Despite the enormous variety and vividness of material perception, it is only just beginning to emerge as a major topic of study in vision research [e.g. 1–7]. Here I present a framework for understanding human visual perception of materials and introduce a number of novel demonstrations of our visual aptitude for estimating material properties. The main thesis I will present is that despite our exquisite sensitivity to changes in physical states (e.g. subtle changes in appearance allow us to tell the difference between fresh and stale bread) the visual system does not generally estimate the intrinsic physical attributes of materials (e.g. density or coefficient of viscosity). Instead, it adopts a heuristic strategy for classifying material appearance based on the statistical behaviour of materials in our environment. In the real world, the observed appearance of a material is subject to constraints such as gravity and natural illumination conditions. Consequently, there exists a large set of simple low-level image measurements (e.g. contrast distributions, amplitude spectra, optic flow patterns, etc.) that reliably correlate with changes in physical state. I will present a taxonomy that organizes these cues, and embed all extant research on material perception within this framework. Broadly I organize the cues into three classes: (1) optical cues, i.e., information arising from the manner in which a material interacts with light, such as its specular reflectance, or sub-surface scattering coefficients. This class of cues has received the most attention, as there is a considerable body of work on the estimation of diffuse albedo and colour. (2) geometric cues, i.e., the characteristic 3D shapes adopted by a material subject to natural forces. (3) dynamic cues, i.e., the way that a material tends to change shape over time or interact with other objects in the scene. I use a variety of physics-based computer graphics simulations to demonstrate these cues and their low-level correlates. Finally I show circumstances under which high-level (cognitive) factors can influence our perception of materials.