Dense Motion Estimation for Smoke

Automated cardiac motion estimation from 3D Cine DENSE MRI

Background 3D cine displacement encoding with stimulated echoes (DENSE) directly encodes tissue displacement into MR phase data, providing a comprehensive 3D view of cardiac motion and strain. Unfortunately, 3D cine DENSE motion analysis presently requires manually delineated anatomy. An automated analysis would reduce interobserver variability, improve measurement throughput, and simplify data...

Video compression with dense motion fields

We propose a motion-compensated video coding system employing dense motion fields. The dense motion field is calculated at the transmitter, and the motion information is efficiently encoded and transmitted along with the residual frame. The motion estimation is performed by existing techniques in the literature, while we focus on the coding of the motion field and the displaced frame difference...

Dense 3D Motion Field Estimation from a Moving Observer in Real Time

In this chapter an approach for estimating the three-dimensional motion fields of real-world scenes is proposed. This approach combines state-of-the-art dense optical flow estimation, including spatial regularization, and dense stereo information using Kalman filters to achieve temporal smoothness and robustness. The result is a dense and accurate reconstruction of the three-dimensional motion ...

A Feature-Based Approach for Determining Dense Long Range Correspondences

Planar motion models can provide gross motion estimation and good segmentation for image pairs with large inter-frame disparity. However, as the disparity becomes larger, the resulting dense correspondences will become increasingly inaccurate for everything but purely planar objects. Flexible motion models, on the other hand, tend to overfit and thus make partitioning difficult. For this reason...

Parallelization of Dense Fluid Motion Estimation Application Using Openmp