This paper is devoted to modelling tissue growth with a deformable cell model. Each cell represents a polygon with particles located at its vertices. Stretching, bending and pressure forces act on particles and determine their displacement. Pressure-dependent cell proliferation is considered. Various patterns of growing tissue are observed. An application of the model to tissue regeneration is ...

| In this paper, we describe models and algorithms designed to produce eecient and physically consistent dynamic simulations. These models and algorithms have been implemented in a unique framework, modeling both deformations and contacts through visco-elastic relations. Since this model of interaction (known as \penalty based") is much debated, we present a detailed study of this model. Indeed...

To date, much research has been done on the manipulation of objects by softfingered robotic hands. Most of these studies, particularly the earlier ones, focused only on contact mechanisms on various soft fingers. More recently, there has been an increase in the number of studies investigating the sensing mechanisms of the human hand and designing control systems in robotic applications to emula...

This paper presents a novel whole body motion tracking method by aligning the 3D model of human body and reconstructed 3D shape of the target obtained from multiple video streams. The advantage of the proposed method is two fold: (1) delicate deformation around shoulder and waist can be accurately tracked by using an articulated deformable model, (2) combination of ICP and robust estimator with...

A geometric approach for 3D object segmentation and representation is presented. The segmentation is obtained by deformable surfaces moving towards the objects to be detected in the 3D image. The model is based on curvature motion and the computation of surfaces with minimal areas, better known as minimal surfaces. The space where the surfaces are computed is induced from the 3D image (volumetr...

Recently, we proposed the generalized active contour model (g-snake) to model and extract deformable contours from noisy images. This paper demonstrates the usefulness of g-snake in classifying among several candidate deformable contours. The g-snake is suitable for this task because its shape representation is unique, aane invariant and possesses metric properties. We derive the optimal classi...

Medical image segmentation is often a diicult task due to the low contrast, the low signal/noise ratio and the presence of outliers in images. However, it remains a critical issue for image interpretation, pattern recognition and automatic diagnosis. Deformable models are well-suited for capturing the geometry and the shape variability of anatomical structures from medical images. Indeed, they ...

In this paper we propose a general approach for performing model-based reconstruction. The task consists in deforming a reference shape in order to extract a geometric model from a 3D dataset. To achieve this goal, two complementary approaches have been widely used. The deformable model framework locally applies internal and external forces to fit 3D data. The non-rigid registration framework i...

Deformable shape models require correspondence across the training population in order to generate a statistical model for use as a future geometric prior. Traditional methods use fixed sampling and assume correspondence, or attempt to induce correspondence by minimizing variance. In this paper, we define a training methodology for sampled medial deformable shape models (m-reps) which generates...