.......................................................................................................................23 Chapter 1 Introduction...............................................................................................25 1.1. Background and Motivations............................................................................25 1.2. Summary of Principle Contributions ........

This paper reviews model based methods for non rigid shape analysis and recognition These methods model match and classify non rigid shapes which are generally problematic for conventional algorithms using rigid models Issues including deformable model represen tation optimization criteria formulation model matching and classi cation are examined in detail The emphasis of this paper is on D def...

Manipulation of deformable objects will be discussed. Manipulation of deformable objects is de ned as controlling deformation of objects as well as their positions and orientations. The manipulation is a fundamental and important task in many industrial elds. In fact, there exist many operations of deformable objects such as textile fabrics, rubber parts, paper sheets, strings, and foods. In or...

Background The use of a medical simulator should enhance the goals of minimally invasive surgery: patient safety, cosmesis, shortening the length of hospital admissions, and reducing cost. Using an innovative approach to the handling of ultrasound images in virtual reality simulation, this article describes a process that employs a hybrid model of deformable models that can be applied in the te...

I. INTRODUCTION We present a symmetry-based method that allows humans and robots to collaboratively manipulate deformable objects. The method does not require modeling and simulating deformation. Our method is based on the concept of diminishing rigidity, which we use to quickly compute an approximation to the Jacobian of the deformable object without using simulation. This Jacobian is used to ...

Using deformable models to register medical images can result in problems of initialization of deformable models and robustness and accuracy of matching of inter-subject anatomical variability. To tackle these problems, a novel model is proposed in this paper by compounding local invariant features and global deformable geometry. This model has four steps. First, a set of highly-repeatable and ...

This paper is the 3rd in a series of papers discussing characterization of a Micro-Electrical-Mechanical-System (MEMS) deformable mirror in adaptive optics. Here we present a comparison between a conventional adaptive optics system using a Xinetics continuous face sheet deformable mirror with that of segmented MEMS deformable mirror. We intentionally designed the optical layout to mimic that of...

We describe a novel approach for image matching based on deformable intensity surfaces. In this approach , the intensity surface of the image is modeled as a deformable 3D mesh in the (x; y; I(x; y)) space. Each surface point has 3 degrees of freedom, thus capturing ne surface changes. A set of representative deformations within a class of objects (e.g. faces) are statistically learned through ...

A probabilistic deformable model for the representation of brain structures is described. The statistically learned deformable model represents the relative location of head (skull and scalp) and brain surfaces in Magnetic Resonance Images (MRIs) and accommodates their significant variability across different individuals. The head and brain surfaces of each volume are parameterized by the ampli...