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Spring 2013 GRASP Seminar: Kristin Dana, Rutgers University, “Illumination Modeling for Camera-Display Communication”

May 3, 2013 @ 11:00 am - 12:00 pm

Abstract: Our
modern society has pervasive electronic displays such as billboards,
tablets, signage and kiosks. The prevalence of these displays provides
opportunities to
develop photographic methods for active scenes where intentional
information is encoded
in the display images and must be recovered by a camera. These active
scenes are fundamentally different from traditional passive scenes
because image formation is based
on display emittance, not surface reflectance. QR-codes on billboards
are one example
of an active scene with intentional information, albeit a very simple
case. The problem
becomes more challenging when the message is hidden and dynamic.
Detecting and
decoding the message requires careful photometric modeling for
computational message
recovery. We present a novel method for communicating between a camera
and display
by embedding and recovering information within a displayed image. A
handheld camera
pointed at the display can receive not only the display image, but also
the underlying
message. Unlike standard watermarking and steganography that lie
outside the domain
of computer vision, our message recovery algorithm uses illumination in
order to op-
tically communicate hidden messages in real world scenes. The key
innovation of our
approach is an algorithm to perform simultaneous radiometric
calibration and message
recovery in one convex optimization problem. By modeling the photometry
of the system using a camera-display transfer function (CDTF), we
derive a physics-based kernel
function for support vector machine classification. We demonstrate that
our method of
optimal online radiometric calibration (OORC) leads to an efficient and
robust algorithm
for a computational messaging between various commercial cameras and
displays. An
evaluation of results has been provided by using video messaging with
nine different
combinations of commercial cameras and displays.


- Learn More

Kristin J. Dana received the PhD from Columbia University (NY,NY) in
1999 and the MS degree from Massachusetts Institute of Technology in
1992, and a BS degree in 1990 from the Cooper Union (NY,NY). She is
an associate professor in the Department of Electrical and Computer
Engineering at Rutgers, The State University of New Jersey. Her
research interests in computer vision include computational
photography, machine learning, illumination modeling, texture and
reflectance, motion estimation, optical devices, optimization in vision
and applications of robotics. Dr. Dana is the inventor of the “texture
camera” for convenient measurement of reflectance and texture. She is
also a member of the Rutgers Center for Cognitive Science and a member
of Graduate Faculty of the Computer Science Department. From
1992-1995 she was on the research staff at Sarnoff Corporation
developing real-time motion estimation algorithms for applications in
defense, biomedicine and entertainment industries. She is the recipient
of the General Electric “Faculty of the Future” fellowship in 1990, the
Sarnoff Corporation Technical Achievement Award in 1994 for the
development of a practical algorithm for the real-time alignment of
visible and infrared video images, and the National Science Foundation
Career Award (2001) for a program investigating surface science for
vision and graphics.


May 3, 2013
11:00 am - 12:00 pm
Event Category: