IJCB 2011 Tutorial: 3D-Aided Face Recognition
Organizers: Ioannis A. Kakadiaris (U of Houston, TX, USA) and Liming Chen (Ecole Centrale de Lyon, Ecully, France)
Speakers:Liming Chen, Ioannis A. Kakadiaris, Shishir Shah
Abstract: The advent of 3D sensors for facial data open new avenues for research in Face Recognition. Specifically it enabled 3D-3D face recognition and 3D-2D face recognition. It this tutorial, we will highlight the challenges and provide an overview of the methods developed from these two classes of problems.
- The participants will understand both the challenges and advantages of using 3D data either as probe or as gallery at a face recognition system.
- 3D sensors
- Facial Modeling and Representation
- Manifold of Faces
- 3D-3D Face Recognition
- denoising and preprocessing
- 3D landmark detection
- similarity metrics and matching
- attribute generation
- 3D-2D Face Recognition
- 2D landmark detection
- illumination normalization
- Challenges and Opportunities
Monday, October 10, 2011
|8:30am to 8:45am||Tutorial Outline and Introductions||IAK and LC|
|8:45am to 9:00am||3D Sensors||LC|
|9:00 am to 9:35am||3D-3D Face Recognition||IAK|
|9:35am to 10:15am||3D-3D Face Recognition||LC|
|10:15am to 10:30am||Break|
|10:30am to 11:10am||3D-2D Face Recognition||IAK and SKS|
|11:10am to 11:50pm||3D-2D Face Recognition||LC|
|11:50am to 12:00pm||Closing Remarks||IAK and LC|
Short Bios of the Organizers
Prof. Ioannis A. Kakadiaris is a Hugh Roy and Lillie Cranz Cullen University Professor of Computer Science, Electrical & Computer Engineering, and Biomedical Engineering at the University of Houston, Houston, TX, USA. He also holds an adjunct position at the School of Health Information Sciences at the University of Texas, Health Sciences Center. He joined UH in August 1997 after a postdoctoral fellowship at the University of Pennsylvania. Ioannis earned his B.Sc. in physics at the University of Athens in Greece, his M.Sc. in computer science from Northeastern University and his Ph. D. at the University of Pennsylvania. He is the founder and director of the Computational Biomedicine Lab. His research interests include non-verbal human behavior understanding, biometrics, computational life sciences, computer vision, and pattern recognition. Dr. Kakadiaris is the recipient of a number of awards, including the NSF Early Career Development Award, Schlumberger Technical Foundation Award, UH Computer Science Research Excellence Award, UH Enron Teaching Excellence Award, and the James Muller Vulnerable Plaque Young Investigator Price. His research has been featured on Discovery Channel, National Public Radio, KPRC NBC News, KTRH ABC News, and KHOU CBS News. Dr. Kakadiaris’ team won the Face Recognition Vendor Test (2007, organized by NIST in 2007) in 3D shape category. He pioneered using 2D images for gallery and 3D models as probes in biometrics applications.
Prof. Liming Chen was awarded the joint B.Sc. degree in mathematics and computer science from the University of Nantes, Nantes, France, in 1984. He obtained the M.S. and Ph.D. degrees in computer science from the University of Paris 6, Paris, France, in 1986 and 1989, respectively. He first served as an Associate Professor at the Université de Technologie de Compiègne, Compiègne, France, and then joined Ecole Centrale de Lyon, Ecully, France, as Professor in 1998, where he leads an advanced research team on multimedia computing and pattern recognition. From 2001 to 2003, he also served as Chief Scientific Officer in a Paris-based company, Avivias, specialized in media asset management. In 2005, he served as Scientific expert multimedia in France Telecom R&D China. He has been the Head of the Department of Mathematics and Computer Science since 2007. He has taken out three patents, authored more than 100 publications, and acted as Chairman, PC member, and reviewer in a number of high profile journals and conferences since 1995. He has been a (co)-principal investigator on a number of research grants from the European Union FP program, French research funding bodies, and local government departments. He has directed more than 15 Ph.D. theses. His current research spans from 2-D/3-D face analysis and recognition and image and video analysis and categorization to affect analysis both in image audio and video.
Shishir K. Shah is Associate Professor of Computer Science at the University of Houston. He received his B.S. degree in Mechanical Engineering, and M.S. & Ph.D. degrees in Electrical and Computer Engineering from The University of Texas at Austin. He directs research at the Quantitative Imaging Laboratory and his current research focuses on fundamentals of computer vision, pattern recognition, and statistical methods in image analysis with applications in multi-modality sensing, video analytics, object recognition, and biomedical image analysis.