Designing a dexterous robotic hand able to interact intelligently with deformable objects constitutes a challenging area of research where many issues are yet to be solved. The complexity of such interactions requires the assistance of intelligent multisensory robotic systems that combine measurements collected from different sensors in order to accurately plan for the forces to be applied on t...

In order to have a good representation of deformable objects, is clever to have an adequate model to represent them. Since the origins of computer graphics, a large number of representation models have been presented. Not all of them are adequate to represent deformable objects. The way in which the objects can be handled, allowing local changes in their shape, or the possibility of the creatio...

Geometric deformable models based on the level set method have become very popular in the last several years. To overcome an inherent limitation in accuracy while maintaining computational efficiency, adaptive grid techniques using local grid refinement have been developed for use with these models. This strategy, however, requires a very complex data structure, yields large numbers of contour ...

Deformable geometric models fit very naturally into the context of Bayesian analysis. The prior probability of boundary shapes is taken to proportional to the negative exponential of the deformation energy used to control the boundary. This probabilistic interpretation is demonstrated using a Markov-Chain Monte-Carlo (MCMC) technique, which permits one to generate configurations that populate t...

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 ...

A method for deformable shape detection and recognition is described. Deformable shape templates are used to partition the image into a globally consistent interpretation, determined in part by the minimum description length principle. Statistical shape models enforce the prior probabilities on global, parametric deformations for each object class. Once trained, the system autonomously segments...

Objects deform in response to contact forces exerted on them. The deformation depends on material properties, the geometry of the object and external forces. This thesis develops a robotic system for automatically acquiring observations of a deforming object and for estimating a model of the deformation from these observations. Models of deformable objects are in wide-spread use in simulation, ...

Introduction: Nowadays virtual colonoscopy has become a reliable and efficient method of detecting primary stages of colon cancer such as polyp detection. One of the most important and crucial stages of virtual colonoscopy is colon segmentation because an incorrect segmentation may lead to a misdiagnosis.  Materials and Methods: In this work, a hybrid method based on Geometric Deformable Models...

In this paper, we propose solutions to real time simulation and interaction of deformable objects in virtual reality. Firstly, we present LEM Long Element Method, a method created for physically based simulation of deformable objects. LEM has been conceived specially for objects filled with fluids. Using Pascal’s Principle and volume conservation, the method produces a static solution for globa...

We present a method for characterizing human activities using 3D deformable shape models. The motion trajectories of points extracted from objects involved in the activity are used to build models for each activity, and these models are used for classification and detection of unusual activities. The deformable models are learnt using the factorization theorem for nonrigid 3D models. We present...