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An ideal locating framework should be able to predict and update the motion state and observation model of an object, and even track multiple objects under various conditions.
In step 5, the original motion-corrupted PET data Y x, t) is registered to the model-predicted PET data Y Φ to update the motion estimation T and motion-corrected PET data Y(T − 1 x), t).
As shown in the figure, when objects move through the image for a specified period, we update the motion history by comparing the current image to the first two images of the vehicle.
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The algorithm essentially updates the motion at previous time using the current image frame as input in a dynamic fashion.
That is we update the equations of motion of individual bubbles.
Furthermore, the system has to repeat all the previous acceleration calculations to update the object's motion displacement.
The proposed D3DR method is designed to work in a real-time environment, not requiring all frames captured to be used to update the recovered 3D motion and structure of the target.
Therefore, the CPU cost of updating the mesh motion could be reduced eventually since it scales with the product of these two numbers.
Given a motion model p ( x t | x t − 1, x ̇ t ) and a sensing model p z t |x t ), we recursively apply a prediction phase where we incorporate motion to update the state and an update phase where the sensing data is used to compute the state's posterior distribution.
PMC was performed by using the motion information to dynamically update the sequence's RF excitation and gradient waveforms such that the field-of-view was realigned to match the subject's head movement.
In this paper, we present two new numerical algorithms for updating the equations of motion for a viscoelastic fluid that can be described by the finite extensible nonlinear elastic polymer model with the closure proposed by Peterlin (so called FENE-P model) in a transient calculation.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com