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Understanding the Role of Phase Function in Translucent Appearance: VCL Lunch Talk - Ioannis Gkioulekas

Seminar: Visual Computing Lab | April 12 | 12-1 p.m. | Soda Hall, Visual Computing Lab - 510 Soda


Ioannis Gkioulekas, Harvard - School of Engineering and Applied Sciences

Electrical Engineering and Computer Sciences (EECS)


ABSTRACT: Multiple scattering contributes critically to the characteristic translucent appearance of food, liquids, skin, and crystals; but little is known about how it is perceived by human observers. This paper explores the perception of translucency by studying the image effects of variations in one factor of multiple scattering: the phase function. We consider an expanded space of phase functions created by linear combinations of Henyey-Greenstein and von Mises-Fisher lobes, and we study this physical parameter space using computational data analysis and psychophysics.

Our study identifies a two-dimensional embedding of the physical scattering parameters in a perceptually-meaningful appearance space. Through our analysis of this space, we find uniform parameterizations of its two axes by analytical expressions of moments of the phase function, and provide an intuitive characterization of the visual effects that can be achieved at different parts of it. We show that our expansion of the space of phase functions enlarges the range of achievable translucent appearance compared to traditional single-parameter phase function models. Our findings highlight the important role phase function can have in controlling translucent appearance, and provide tools for manipulating its effect in material design applications.

Joint work with Bei Xiao, Shuang Zhao, Edward Adelson, Todd Zickler, and Kavita Bala.

Bio: Ioannis Gkioulekas is a PhD candidate in Electrical Engineering at the Harvard School of Engineering and Applied Sciences, where he works with Prof. Todd Zickler. He has received a Master of Science from Harvard and a diploma in Electrical and Computer Engineering from the National Technical University of Athens, Greece. His research interests include computer vision (visual sensors for micro platforms, modeling and analysis of hyperspectral images), statistical machine learning (dimensionality reduction, kernel methods, dictionary models), and computer graphics (perception, acquisition and rendering of
translucent materials).


510-643-2614