IEEE Trans Image Process - Computation of fluid and particle motion from a time-sequenced image pair: a global outlier identification approach.

Tópicos

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Resumo

Fluid motion estimation from time-sequenced images is a significant image analysis task. Its application is widespread in experimental fluidics research and many related areas like biomedical engineering and atmospheric sciences. In this paper, we present a novel flow computation framework to estimate the flow velocity vectors from two consecutive image frames. In an energy minimization-based flow computation, we propose a novel data fidelity term, which: 1) can accommodate various measures, such as cross-correlation or sum of absolute or squared differences of pixel intensities between image patches; 2) has a global mechanism to control the adverse effect of outliers arising out of motion discontinuities, proximity of image borders; and 3) can go hand-in-hand with various spatial smoothness terms. Further, the proposed data term and related regularization schemes are both applicable to dense and sparse flow vector estimations. We validate these claims by numerical experiments on benchmark flow data sets.

Resumo Limpo

fluid motion estim timesequenc imag signific imag analysi task applic widespread experiment fluidic research mani relat area like biomed engin atmospher scienc paper present novel flow comput framework estim flow veloc vector two consecut imag frame energi minimizationbas flow comput propos novel data fidel term can accommod various measur crosscorrel sum absolut squar differ pixel intens imag patch global mechan control advers effect outlier aris motion discontinu proxim imag border can go handinhand various spatial smooth term propos data term relat regular scheme applic dens spars flow vector estim valid claim numer experi benchmark flow data set

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