Event Location: NSH 3305
Bio: Lavanya Sharan is a final year graduate student working with Ted Adelson at
MIT. Her research interests lie at the intersection of human vision and
computer vision, especially in the domain of material recognition. She is
interested in understanding how humans can recognize the materials that
objects are made of and how to make computer vision systems that can do the
same. Lavanya received her M.S. degree in Computer Science from MIT in 2005
and her undergraduate training in Electrical Engineering from IIT Delhi in
2003.

Abstract: We can easily tell if a spoon is made of stainless steel or
plastic, if a shirt is clean or if food is fresh. These judgments of
material appearance are ubiquitous. We use our material perception abilities
to decide where to step on an icy sidewalk, which items to pick in the fresh
produce aisle, and if a rash requires a trip to the doctor. In spite of the
importance of these judgments, little is known about material recognition in
the fields of human vision or computer vision.

We have studied human material judgments on real world photographs by asking
observers questions like “Is that object made of paper or plastic?” or “Are
those flowers fake or real?”. We find that observers can recognize materials
very well, even when images are presented very fast (40 millisecond/image).
This performance was robust to low-level image degradations like removal of
color, blurring and inversion of contrast polarity, suggesting that
low-level information is not crucial for observers.

What do these results imply for machine vision systems? We evaluated the
performance of simple classifiers based on low-level image features (e.g.
jet-like features, SIFT) at the same material categorization task that
humans did. We find that low-level features are not sufficient for
categorizing materials on our data set suggesting a parallel with the
results from human experiments. We conclude that there is rich territory to
be explored both by computer vision and human vision researchers for this
problem.