In this paper, we present a new technique of 3D face reconstruction from a sequence of images taken with cameras having varying parameters without the need to grid. This method is based on the estimation of the projec...In this paper, we present a new technique of 3D face reconstruction from a sequence of images taken with cameras having varying parameters without the need to grid. This method is based on the estimation of the projection matrices of the cameras from a symmetry property which characterizes the face, these projections matrices are used with points matching in each pair of images to determine the 3D points cloud, subsequently, 3D mesh of the face is constructed with 3D Crust algorithm. Lastly, the 2D image is projected on the 3D model to generate the texture mapping. The strong point of the proposed approach is to minimize the constraints of the calibration system： we calibrated the cameras from a symmetry property which characterizes the face, this property gives us the opportunity to know some points of 3D face in a specific well-chosen global reference, to formulate a system of linear and nonlinear equations according to these 3D points, their projection in the image plan and the elements of the projections matrix. Then to solve these equations, we use a genetic algorithm which consists of finding the global optimum without the need of the initial estimation and allows to avoid the local minima of the formulated cost function. Our study is conducted on real data to demonstrate the validity and the performance of the proposed approach in terms of robustness, simplicity, stability and convergence.展开更多
The soil-rock mixture(SRM) is highly heterogeneous. Before carrying out numerical analysis,a structure model should be generated. A reliable way to obtain such structure is by generating random aggregate structure bas...The soil-rock mixture(SRM) is highly heterogeneous. Before carrying out numerical analysis,a structure model should be generated. A reliable way to obtain such structure is by generating random aggregate structure based on random sequential addition(RSA). The classical RSA is neither efficient nor robust since valid positions to place new inclusions are formulated by trial, which involves repetitive overlapping tests. In this paper, the algorithm of Entrance block between block A and B(EAB)is synergized with background mesh to redesign RSA so that permissible positions to place new inclusions can be predicted,resulting in dramatic improvement in efficiency and robustness.展开更多
An adaptive meshing technique and solution method is proposed in which a two-dimensional body-fitted multi-block mesh is locally adjusted to arbitrarily embedded boundaries that are not necessarily aligned with the me...An adaptive meshing technique and solution method is proposed in which a two-dimensional body-fitted multi-block mesh is locally adjusted to arbitrarily embedded boundaries that are not necessarily aligned with the mesh.Not only does this scheme allow for rapid and robust mesh generation involving complex embedded boundaries,it also enables the solution of unsteady flow problems involving bodies and interfaces moving relative to the flow domain.This scheme has been implemented within a block-based adaptive mesh refinement(AMR)numerical framework which can ease computational expense while maintaining a detailed representation of the embedded boundary and providing an accurate resolution of the spatial characteristics of the fluid flow.Rigid body motion and evolving motion due to physical processes are considered.A block-based AMR level set method is used to deal with evolving embedded boundaries.Numerical results for various test problems are presented to verify the validity of the scheme as well as demonstrate the capabilities of the approach for predicting complex two-dimensional inviscid and laminar fluid flows.展开更多
文摘In this paper, we present a new technique of 3D face reconstruction from a sequence of images taken with cameras having varying parameters without the need to grid. This method is based on the estimation of the projection matrices of the cameras from a symmetry property which characterizes the face, these projections matrices are used with points matching in each pair of images to determine the 3D points cloud, subsequently, 3D mesh of the face is constructed with 3D Crust algorithm. Lastly, the 2D image is projected on the 3D model to generate the texture mapping. The strong point of the proposed approach is to minimize the constraints of the calibration system： we calibrated the cameras from a symmetry property which characterizes the face, this property gives us the opportunity to know some points of 3D face in a specific well-chosen global reference, to formulate a system of linear and nonlinear equations according to these 3D points, their projection in the image plan and the elements of the projections matrix. Then to solve these equations, we use a genetic algorithm which consists of finding the global optimum without the need of the initial estimation and allows to avoid the local minima of the formulated cost function. Our study is conducted on real data to demonstrate the validity and the performance of the proposed approach in terms of robustness, simplicity, stability and convergence.
基金supported by the National Basic Research Program of China(973 Program)(Grant No.2014CB047100)the National Natural Science Foundation of China(Grant Nos.11572009,51538001 and 51609240)
文摘The soil-rock mixture(SRM) is highly heterogeneous. Before carrying out numerical analysis,a structure model should be generated. A reliable way to obtain such structure is by generating random aggregate structure based on random sequential addition(RSA). The classical RSA is neither efficient nor robust since valid positions to place new inclusions are formulated by trial, which involves repetitive overlapping tests. In this paper, the algorithm of Entrance block between block A and B(EAB)is synergized with background mesh to redesign RSA so that permissible positions to place new inclusions can be predicted,resulting in dramatic improvement in efficiency and robustness.
基金supported by a Premier’s Research Excellence Award from the Ontario Ministry of Energy,Science,and Technology and by the Natural Sciences and Engineering Research Council of CanadaFunding for the parallel computing facility used to perform the computations described herein was obtained from the Canadian Foundation for Innovation and Ontario Innovation Trust(CFI Project No.2169)。
文摘An adaptive meshing technique and solution method is proposed in which a two-dimensional body-fitted multi-block mesh is locally adjusted to arbitrarily embedded boundaries that are not necessarily aligned with the mesh.Not only does this scheme allow for rapid and robust mesh generation involving complex embedded boundaries,it also enables the solution of unsteady flow problems involving bodies and interfaces moving relative to the flow domain.This scheme has been implemented within a block-based adaptive mesh refinement(AMR)numerical framework which can ease computational expense while maintaining a detailed representation of the embedded boundary and providing an accurate resolution of the spatial characteristics of the fluid flow.Rigid body motion and evolving motion due to physical processes are considered.A block-based AMR level set method is used to deal with evolving embedded boundaries.Numerical results for various test problems are presented to verify the validity of the scheme as well as demonstrate the capabilities of the approach for predicting complex two-dimensional inviscid and laminar fluid flows.
