Jason Saragih

Research Scientist

Contact

Science Area

• Imaging and Computer Vision

Biography

Jason Saragih is a Research Scientist at the CI2CV computer vision group at the Commonwealth Scientific and Research Organisation (CSIRO), Australia. His research in Computer Vision has focused primarily on the use of learning in deformable object registration and recognition, with particular emphasis on applications in Human-Computer Interfaces. He is the author of two publicly available deformable object modelling API’s; DeMoLib and FaceTracker. He obtained his doctoral degree from the Australian National University in 2008 and spent two years as a Post-doctoral Fellow at the Robotics Institute, at Carnegie Mellon University.

Academic Qualifications

2008	PhD Australian National University, Computer Science and Technology 2004 BEng Australian National University, Mechatronics Engineering

Recent Professional Experience

2010-Current

Research Scientist, ICT Centre 2008-2010 Postdoctoral Research Scientist, Robotics Institute, CMU

Achievements & Awards

2004-2007

Australian Research Council Grant Ph.D. Scholarship 2000-2003 Australian National University Undergraduate Scholarship 1999 V. J. Brown Memorial Prize for Academic Excellence, University of Newcastle

Summary of Science & Technical Output

Top 10 Publications

Publication details
J. Saragih, S. Lucey and J. Cohn, “Deformable Model Fitting by Regularized Landmark Mean-Shifts”, International Journal of Computer Vision (IJCV), 91(2): 200–215, 2010.
J. Saragih and R. Goecke, “Learning AAM Fitting through Simulation”, Journal of Pattern Recognition (PR), 42(11): 2628–2636, 2009
J.Saragih,“PrincipalRegressionAnalysis”,IEEEInternationalConferenceonComputerVision and Pattern Recognition (CVPR), 2011
J.Saragih,S.Lucey,andJ.Cohn,“FaceAlignmentthroughSubspaceConstrainedMean-Shifts”, IEEE International Conference on Computer Vision (ICCV), 2009
J. Saragih and R. Goecke, “A Nonlinear Discriminative Approach to AAM Fitting”, IEEE International Conference on Computer Vision (ICCV), 2007
J. Saragih and R. Goecke, “Monocular and Stereo Methods for AAM Learning from Video”, IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), 2007
S. Lucey, Y. Wang, J. Saragih and J. Cohn, “Non-rigid Face Tracking with Enforced Convex- ity and Local Appearance Consistency Constraint”, International Journal of Image and Vision Computing (IVC), 28(5): 781–789, 2010
J. Saragih, S. Lucey, and J. Cohn, “Real-Time Avatar Animation from a Single Image”, IEEE International Conference on Automatic Face and Gesture Recognition (AFGR), 2011
J. Saragih, S. Lucey and J. Cohn, “Deformable Model Fitting with a Mixture of Local Experts”, IEEE International Conference on Computer Vision (ICCV), 2009
J. Saragih and R. Goecke, “Iterative Error Bound Minimisation for AAM Alignment”, Inter- national Conference on Pattern Recognition (ICPR), 2006

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