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Thanks to Bayes' theorem, any image processing problem involves two parts: a model of the image, given the semantics one is seeking, and a prior model of this semantics. Many problems involve a semantics of the form 'the volume in the world that projected to the region R in the image had parameters P', and thus models of regions, and models of images within regions, acquire great importance. My current research focuses on the construction of such models.
Shape modelling via higher-order active contours and phase fields
as author at MUSCLE Conference joint with VITALAS Conference,