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Spring 2013 GRASP Seminar: Kristin Dana, Rutgers University, "Illumination Modeling For Camera-Display Communication"
Presenter: Kristin Dana (Homepage)
Friday May 3, 2013 from 11:00am to 12:00pm
Our modern society has pervasive electronic displays such as billboards, computers, 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.
Dr. 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.