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Generalized fast marching method: applications to image segmentation
Numerical Algorithms, 2008zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Forcadel, Nicolas +2 more
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Optimal control using the Fast Marching Method
2009 35th Annual Conference of IEEE Industrial Electronics, 2009This paper presents the applications of the Fast Marching and the Buffered Fast Marching Methods to solve typical control problems. Calculus of Variations and Optimal Control problems can be solved using the Euler-Lagrange or the Pontryagin equations and solving analytically or numerically the corresponding differential equations systems.
Santiago Garrido +3 more
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Robust skeletonization using the fast marching method
IEEE International Conference on Image Processing 2005, 2005We have recently developed a level set based-framework for computing medial curves or curve skeletons CS for arbitrary 2D shapes as well as tubular and articulated 3D objects. The proposed framework is robust, fully automatic, computationally efficient, and produces curve skeletons that are connected, centered, thin, and less sensitive to boundary ...
M.S. Hassouna, A.A. Farag
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A Massive Parallel Fast Marching Method
2016In this paper we present a novel technique based on domain decomposition which enables us to perform the fast marching method (FMM) [4] on massive parallel high performance computers (HPC) for given triangulated geometries. The FMM is a widely used numerical method and one of the fastest serial state-of-the-art techniques for computing the solution to ...
Petr Kotas +4 more
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A fast marching method for reservoir simulation
Computational Geosciences, 2000zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Karlsen, K. Hvistendahl +2 more
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2004
The fast marching method was introduced by Sethian [190, 191, 192] as a computationally efficient solution to eikonal equations on flat domains. A related method was presented by Tsitsiklis in [205]. The fast marching method was extended to triangulated surfaces by Kimmel and Sethian in [112].
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The fast marching method was introduced by Sethian [190, 191, 192] as a computationally efficient solution to eikonal equations on flat domains. A related method was presented by Tsitsiklis in [205]. The fast marching method was extended to triangulated surfaces by Kimmel and Sethian in [112].
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A Generalized Fast Marching Method on Unstructured Triangular Meshes
SIAM Journal on Numerical Analysis, 2013In this paper we extend the generalized fast marching method (GFMM) presented in [E. Carlini et al., SIAM J. Numer. Anal., 46 (2008), pp. 2920--2952] to unstructured meshes. The GFMM generalizes the classical fast marching method, in the sense that it can be applied to propagate interfaces with time-dependent and changing sign velocity.
CARLINI, Elisabetta +2 more
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Three Dimensional Traveltimes Using the Fast Marching Method
60th EAGE Conference and Exhibition, 1998A fast, accurate and unconditionally stable 3-D traveltime algorithm is an important tool in seismic imaging. Applications of a robust traveltime computation module are not limited to 3-D Kirchhoff prestack and poststack migration, but also can be used for 3-D velocity analysis, 3-D Kirchoff modeling, 3-D Kirchhoff datuming, and 3-D variable velocity ...
M. Popovici, J. Sethian
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Shape from self-calibration and Fast Marching Method
2008 19th International Conference on Pattern Recognition, 2008Shape-from-shading methods recover 3-D shape from intensity images. Often, Lambertian reflectance is assumed. The Lambertian assumption is attractive because it simplifies the analysis. Alternatively, non-Lambertian reflectance, including specularity, is accommodated in methods that measure reflectance empirically either using a separate calibration ...
Yuji Iwahori +4 more
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Guided depth enhancement via a fast marching method
Image and Vision Computing, 2013Range imaging sensors such as Kinect and time-of-flight cameras can produce aligned depth and color images in real time. However, the depth maps captured by such sensors contain numerous invalid regions and suffer from heavy noise. These defects more or less influence the use of depth information in practical applications. In order to enhance the depth
Xiaojin Gong +3 more
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