Recent advances in deformable models have lead to new classes of methods that borrow the best features form level sets as well as traditional parametric deformable models. In this talk I will first present a new class of such models termed Metamorphs whose formulation integrates shape, intensity and texture by borrowing ideas from level sets and traditional parametric deformable models. Further extensions to these models include the inclusion of shape and texture priors. These new models can be used in medical segmentation and registration where organ boundaries are fuzzy and with no assumptions on the noise distribution. In the second part of the talk I will present novel body and face tracking methods based within a generative and/or discriminative modeling framework.
Dr. Dimitris Metaxas is a Professor in the Division of Computer & Information Sciences and Professor in the Department of Biomedical Engineering at Rutgers University since 2001. He is also directing the Center for Computational Biomedicine, Imaging and Modeling (CBIM). Dr. Metaxas has been conducting research towards the development of formal methods upon which computer vision, computer graphics and medical imaging can advance synergistically. His focus is on the development of novel deformable models and algorithms for segmentation, registration, tracking, recognition and simulation in the above areas. Dr. Metaxas has published over 200 research articles in these areas and has graduated 20 PhD students. His research on the modeling of the heart and on fluid modeling has received several best papers awards. He is a recipient of an ONR YIP and is a Fellow of the American Institute of Medical and Biological Engineers. He is also the program chair of ICCV 2007 and the general chair of MICCAI 2008.
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