Event Location: NSH 1507
Bio: Sameer Agarwal received the M.S. degree in Mathematics and Scientific
Computation from the Indian Institute of Technology, Kanpur in 2000
and a PhD in Computer Science from the University of California, San
Diego in 2006. He is currently a postdoc in the Computer Science and
Engineering Department at University of Washington, Seattle. His
research interests include computer vision, machine learning and
optimization, though not necessarily in that order.

Abstract: As we make progress in measuring and modeling reflectance, it is
also important that we develop a better understanding of how the
human visual system perceives the reflection of light. Such a
development not only has implications for efficient image synthesis,
but also for computer vision where an understanding of reflectance
perception will give us insight into the priors and constraints used
by humans to solve various shading related problems, e.g., shape
from shading and object recognition over variable and unknown lighting.

In this talk I will present a study of the perception of
reflectance. I will argue that our methodology based on paired
comparisons is better suited for capturing human perception and is
less susceptible to experimental errors than previously used
methods. The analysis of paired comparisons required the development
of a new data analysis tool. In the second part of the talk I will
present a new multidimensional scaling algorithm for analyzing
paired comparisons. Based on semi-definite programming, this
algorithm is a more general and efficient replacement for the widely
used Non-metric MDS algorithm.

Using this algorithm we obtain a perceptual embedding of BRDFs from
the MIT/MERL Database. This embedding, constructed purely from
psychophysical data, exhibits some striking correlations with the
material appearance standards that have been developed independently
in the paper and paint industries. Finally, I will describe a novel
perceptual interpolation scheme that uses this embedding to provide
the user with an intuitive interface for navigating the space of
reflectances and constructing new ones.