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In this paper, we propose a new PDE-based methodology for deformable surfaces that is capable of automatically evolving its shape to capture the geometric boundary of the data and simultaneously discover its underlying topological structure. Our model can handle multiple types of data (such as volumetric data, 3D point clouds and 2D image data), using a(More)
In this paper, we propose a new shape-modeling paradigm based on the concept of Lagrangian surface flow. Given an input polyg-onal model, the user interactively defines a distance field around regions of interest; the locally or globally affected regions will then automatically deform according to the user-defined distance field. During the deformation(More)
This paper presents a surface reconstruction algorithm that can recover correct shape geometry as well as its unknown topology from both volumetric images and unorganized point clouds. The algorithm starts from a simple seed model (of genus zero) that can be arbitrarily initiated within any datasets. The deformable behavior of the model is governed by a(More)
In this paper, we develop a novel subdivision-based model—Intelligent Balloon—which is capable of recovering arbitrary, complicated shape geometry as well as its unknown topology simultaneously. Our Intelligent Balloon is a parameterized subdivision surface whose geometry and its deformable behaviors are governed by the principle of energy(More)
This paper presents a novel, powerful reconstruction algorithm that can recover correct shape geometry as well as its unknown topology from arbitrarily complicated volumetric datasets. The algorithm starts from a simple seed model (of genus zero) that can be initialized automatically without user intervention. The deformable behavior of the model is then(More)
—Medical image segmentation has become an essential technique in clinical and research-oriented applications. Because manual segmentation methods are tedious, and fully automatic segmentation lacks the flexibility of human intervention or correction, semi-automatic methods have become the preferred type of medical image segmentation. We present a hybrid,(More)
Chinese Medicine (TCM) has a long history and has been recognized as a popular alternative medicine in western countries. Tongue diagnosis is a significant procedure in computer-aided TCM, where tongue image analysis plays a dominant role. In this paper, we proposed a fully automatic tongue detection and tongue segmentation framework, which is an essential(More)
In this paper, we present a new deformable model — 2.5D Active Contour— that is capable of directly extracting shape geometry from 3D unorganized point cloud datasets. The reconstructed surfaces are either open or closed. Furthermore, the new model can reconstruct and discover non-manifold geometry hidden in the point-cloud dataset. Our algorithm starts(More)