Tuesday, January 4, 2011
5:45 p.m. – Networking Reception
6:30 p.m. – Presentation
Automated human face recognition using digital 2D and/or 3D photographs is a non-trivial computer vision problem of considerable practical significance. It has numerous applications including automated secured access to ATM machines and buildings, surveillance, forensic analysis, fast retrieval of records from databases in police departments, automatic identification of patients in hospitals, checking for fraud or identity theft, social networking, and human/computer interaction.
Over the past three decades, considerable research has been directed toward developing reliable automatic face recognition systems; now, commercial systems are also available for 2D face recognition that employ digital photographs. The current decade has seen the emergence of 3D face recognition technologies. In part, this emergence has been due to the availability of improved, less expensive 3D imaging devices and processing algorithms.
In this talk, Dr. Shalini Gupta will provide an understanding of the challenges, concepts, and mechanisms of automated face recognition systems. She will present a historical perspective on the advancement of face recognition technology—its milestones and its current state-of-the-art. In addition, she will discuss recent contributions that she and her team have made at the Laboratory of Image and Video Engineering and the Biomedical Informatics Laboratory at The University of Texas at Austin, and will conclude with thoughts on future trends.
Dr. Gupta received a bachelor’s degree in Electronics and Electrical Communication Engineering from Punjab Engineering College, India, in 2002, and master’s and doctoral degrees in Electrical and Computer Engineering from The University of Texas at Austin in 2004 and 2008, respectively. She worked under the supervision of Dr. Alan C. Bovik at the UT Laboratory for Image and Video Engineering, and Dr. Mia K. Markey at the UT Biomedical Informatics Laboratory. As a part of her graduate work, she developed successful algorithms for 3D human face recognition and for the computer aided diagnosis of breast cancer using mammography images. She has published numerous journal and conference articles on these topics.
Currently, she works in the Architecture, Service Concepts and Video Group at AT&T Laboratories on video compression and video quality assessment for AT&T’s U-Verse service. She also worked as an Imaging and Architecture Scientist at the Wireless Division of Texas Instruments, where she designed wireless camera image processing algorithms.