32-Issue 2

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https://diglib.eg.org/handle/10.2312/180

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Browsing 32-Issue 2 by Subject "Curve"

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    Bilateral Hermite Radial Basis Functions for Contour-based Volume Segmentation
    (The Eurographics Association and Blackwell Publishing Ltd., 2013) Ijiri, Takashi; Yoshizawa, Shin; Sato, Yu; Ito, Masaaki; Yokota, Hideo; I. Navazo, P. Poulin
    In this paper, we propose a novel contour-based volume image segmentation technique. Our technique is based on an implicit surface reconstruction strategy, whereby a signed scalar field is generated from user-specified contours. The key idea is to compute the scalar field in a joint spatial-range domain (i.e., bilateral domain) and resample its values on an image manifold. We introduce a new formulation of Hermite radial basis function (HRBF) interpolation to obtain the scalar field in the bilateral domain. In contrast to previous implicit methods, bilateral HRBF (BHRBF) generates a segmentation boundary that passes through all contours, fits high-contrast image edges if they exist, and has a smooth shape in blurred areas of images. We also propose an acceleration scheme for computing B-HRBF to support a real-time and intuitive segmentation interface. In our experiments, we achieved high-quality segmentation results for regions of interest with high-contrast edges and blurred boundaries.
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    Coupled Quasi-harmonic Bases
    (The Eurographics Association and Blackwell Publishing Ltd., 2013) Kovnatsky, Artiom; Bronstein, Michael M.; Bronstein, Alexander M.; Glashoff, Klaus; Kimmel, Ron; I. Navazo, P. Poulin
    The use of Laplacian eigenbases has been shown to be fruitful in many computer graphics applications. Today, state-of-the-art approaches to shape analysis, synthesis, and correspondence rely on these natural harmonic bases that allow using classical tools from harmonic analysis on manifolds. However, many applications involving multiple shapes are obstacled by the fact that Laplacian eigenbases computed independently on different shapes are often incompatible with each other. In this paper, we propose the construction of common approximate eigenbases for multiple shapes using approximate joint diagonalization algorithms, taking as input a set of corresponding functions (e.g. indicator functions of stable regions) on the two shapes. We illustrate the benefits of the proposed approach on tasks from shape editing, pose transfer, correspondence, and similarity.