On account of having real-time behavior and being easy to implement, spring meshes have been used for modeling deformable objects. Determining spring stiffness parameters for simulation of soft objects with high accuracy still remains a challenge. Allen Van Gelder derived an approximate formula for determining spring stiffness parameters based on strain analysis. Even though the experimental re...

Low count tetrahedral meshes is desirable for animating deformable objects where accuracy is less important and to produce shell maps. This report develops a new method for creating a thick shell tetrahedral mesh from a triangular surface mesh. We propose to use signed distance fields to implicit represent the medial surface representation of a surface mesh. An iteratively algorithm is develope...

A new type of deformable model is presented that merges meshes and level sets into one representation to provide interoperability between methods designed for either. The key idea is to use a constellation of triangular surface elements (springls) to define a level set. A Spring Level Set (SpringLS) can be interpreted as a mesh or level set and used in place of them in many instances. There is ...

We propose an improved shape matching algorithm that extends the work of Felzenszwalb [3]. In this approach, we use triangular meshes to represent deformable objects and use dynamic programming to find the optimal mapping from the source image to the target image which minimizes a new energy function. Our energy function includes a new cost term that takes into account the center of mass of an ...

We present an efficient and accurate algorithm for self-collision detection in deformable models. Our approach can perform discrete and continuous collision queries on triangulated meshes. We present a simple and linear time algorithm to perform the normal cone test using the unprojected 3D vertices, which reduces to a sequence point-plane classification tests. Moreover, we present a hierarchic...

3D meshes are widely employed to represent geometry structure of shapes. Due limitation scanning sensor precision and other issues, inevitably affected by noise, which hampers the subsequent applications. Convolultional neural networks (CNNs) achieve great success in image processing tasks, including 2D denoising, have been proven own capacity modeling complex features at different scales, is a...

Image segmentation of 3D medical images is a challenging problem with several still not totally solved practical issues, such as noise interference, variable object structures and image artifacts. This paper describes a hybrid 3D image segmentation method which combines region growing and deformable models toobtainaccurate and topologicallypreserving surface structuresof anatomical objects of i...

In this paper we address the problem of rapid distance computation between rigid objects and highly deformable objects, which is important in the context of physically based modeling of e.g hair or clothing. Our method is in particular useful when modeling deformable objects with particle systems—the most common approach to simulate such objects. We combine some already known techniques about d...

In previous work by the authors, Spectral Difference Method has been formulated in a framework with time-dependent moving deformable meshes. The framework has also been shown to preserve the design accuracy of the underlying high order temporal (explicit Runge-Kutta) and spatial discretization (Spectral Difference) methods. In this study, Spectral Difference method is further extended to deal w...

In the field of 3D images, relevant information can be difficult to interpret without further computer-aided processing. Generally, and this is particularly true in medical imaging, a segmentation process is run and coupled with a visualization of the delineated structures to help understanding the underlying information. To achieve the extraction of the boundary structures, deformable models a...