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The diagnosis of left ventricular mechanical dyssynchrony (LVMD) and identifying cardiac resynchronization therapy (CRT) candidates are challenging problems due to the limitation of the currently applied regional volume-curve analysis. In this study, four-dimensional (4D, 3D+time) left ventricle (LV) regional shape models of 26 LVMD patients were constructed from pre- and/or post- CRT real-time 3D...
We present a method that is capable of tracking and estimating pose of articulated objects in real-time. This is achieved by using a bottom-up approach to detect instances of the object in each frame, these detections are then linked together using a high-level a priori motion model. Unlike other approaches that rely on appearance, our method is entirely dependent on motion; initial low-level part...
This paper presents a method that is capable of robustly estimating gait phase of a human walking from a sequence of images using only low-level motion. The approach we adopt is first to learn statistical motion models of the trajectories we would expect to observe for each of the main limbs. We then extract a sparse cloud of motion features from an image sequence using a standard feature tracker...
Research has shown that the dynamics of facial motion are important in the perception of gender, identity, and emotion. In this paper we show that it is possible to use a multilinear tensor framework to extract facial motion signatures and to cluster these signatures by gender or by emotion. Here we consider only the dynamics of internal features of the face (e.g. eyebrows, eyelids and mouth) so as...
We present a novel approach to motion synthesis. It is shown that by splitting sequences into segments new sequences can be created with a similar look and feel to the original. Copying segments of the original data generates a sequence which maintains detailed characteristics. By modelling each segment using an autoregressive process we can introduce new segments and therefore unseen motions. These...
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