We present a statistical method for the motion-based segmentation of deformable structures undergoing nonrigid movements. The proposed approach relies on two models describing the shape of interest, its variability, and its movement. The first model corresponds to a statistical deformable template that constrains the shape and its deformations. The second model is introduced to represent the op...

As objects are inherently 3-dimensional, they have been modeled in 3D in the early days of computer vision. Due to the ambiguities arising from mapping 2D features to 3D models, 2D feature-based models are the predominant paradigm in object recognition today. While such models have shown competitive bounding box (BB) detection performance, they are clearly limited in their capability of fine-gr...

We present a new mathematical formulation for curve and surface reconstruction algorithms by introduction of auxiliary variables. For deformable models and templates, two-step iterative algorithms have been often used where, at each iteration, the model is first locally deformed according to the potential data attraction and then globally smoothed. We show how these approaches can be interprete...

In this paper an overview of functionally graded materials and constitutive relations of electro elasticity for three-dimensional deformable  solids is presented, and  governing equations of the Bernoulli–Euler and Timoshenko beam theories which account for through-thickness power-law variation of a two-constituent material and piezoelectric layers are developed  using the  principle  of virtua...

Deformable models are used in many computer graphic and animation applications, such as virtual environments, video games, medical simulations, and engineering analysis. Techniques for simulating deformable objects often require a mesh of discrete, tetrahedral elements that represent the object being modeled. This paper describes the implementation of a fast and robust method to generate a tetr...

We present a formal methodology for the integration of optical flow and deformable models. The optical flow constraint equation provides a non-holonomic constraint on the motion of the deformable model. In this augmented system, forces computed from edges and optical flow are used simultaneously. When this dynamic system is solved, a model-based least-squares solution for the optical flow is ob...

Previously, “Deformable organisms” were introduced as a novel paradigm for medical image analysis that uses artificial life modelling concepts. Deformable organisms were designed to complement the classical bottomup deformable models methodologies (geometrical and physical layers), with top-down intelligent deformation control mechanisms (behavioral and cognitive layers). However, a true physic...

Image segmentation is the process of separating or grouping an image into different parts . These parts normally correspond to something that human beings can easily separate and view as individual objects. Computers have no means of intelligently for recognizing objects, and a large number of different methods have been developed in order to segment images, ranging from the simple thresholding...

This practice and experience paper describes a robust C++ implementation of several nonlinear solid 3D deformable object strategies commonly employed in computer graphics, named the Vega FEM simulation library. Deformable models supported include co-rotational linear FEM elasticity, Saint-Venant Kirchhoff FEM model, mass-spring system, and invertible FEM models: neo-Hookean, Saint-Venant Kirchh...

ÐA 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 segment...