Ecaterina Bodnariuc

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We present a novel approach to detect the trajectories of particles by combining (a) adaptive dictionaries that model physically consistent spatio-temporal events, and (b) convex programming for sparse matching and trajectory detection in image sequence data. The mutual parametrization of these two components are mathematically designed so as to achieve(More)
We present a simple and efficient approach to plane wave ultrasound particle image velocimetry (Echo PIV). Specifically, a carefully designed bank of local motion-sensitive filters is introduced, together with a method for non-linear flow parameter estimation based on timeaveraged local flow estimates. The approach is validated and quantitatively assessed(More)
We introduce a novel motion estimation approach for Echo PIV for the laminar and steady flow model. We mathematically formalize the motion estimation problem as a parametrization of a dictionary of particle trajectories by the physical flow parameter. We iteratively refine this unknown parameter by subsequent sparse approximations. We show smoothness of the(More)
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