Statistical shape modeling using point distribution models (PDMs) has been studied extensively for segmentation and other image analysis tasks. Methods investigated in the literat...
Geremy Heitz, Torsten Rohlfing, Calvin R. Maurer J...
Point Distribution Models are useful tools for modelling the variability of particular classes of shapes. A common approach is to apply a Principle Component Analysis to the data,...
James Orwell, Darrel Greenhill, Jonathan D. Rymel,...
In this paper we apply state-of-the-art approach to object detection and localisation by incorporating local descriptors and their spatial configuration into a generative probabil...
Joni-Kristian Kamarainen, Miroslav Hamouz, Josef K...
Kernel machines have recently been considered as a promising solution for implicit surface modelling. A key challenge of machine learning solutions is how to fit implicit shape mo...
In this paper, we propose a novel explicit 2D+t cyclic shape model that extends the Point Distribution Model (PDM) to shapes like myocardial contours with cyclic dynamics. We also ...