Fast facial points fitting plays an important role in applications such as Human-Computer Interaction, entertainment, surveillance, and is highly relevant to the techniques of facial expression analysis, face recognit...
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Fast facial points fitting plays an important role in applications such as Human-Computer Interaction, entertainment, surveillance, and is highly relevant to the techniques of facial expression analysis, face recognition, 3D face model generation, etc. Active Appearance Models (AAMs) are generative models commonly used to fit face. They are sensitive to illumination and expression changes because they use only raw intensity to build observation models. In this paper, a real time facial points fitting approach using mixture observation models is presented. Furthermore, the 3D modes are used to constrain the AAM so that it can only generate model instances that can also be generated with the 3D modes. Finally, we give a derivative process for fast energy minimization using the inverse compositional algorithm. A coarse-to-fine fitting strategy is used for realtime and robust facial points fitting. We apply this algorithm to facial expression cloning of 3D Avatar system. Experimental results demonstrate that fitting the AAM with mixture observation models and 3D constraint outperforms other classical algorithms.
This article investigates how the Empirical Mode Decomposition (EMD) algorithm, a newly-developed and effective technique in the fields of signal processing and time-frequency analysis, is introduced and applied to ac...
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A new multidomain pseudospectral frequency-domain (PSFD) method based on Legendre polynomials with a penalty scheme for studying electromagnetic wave scattering is presented. Scattered field calculation with accuracy ...
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The high-accuracy pseudospectral time-domain (PSTD) method is utilized to simulate electromagnetic responses of two-dimensional (2D) optical microring resonators. Besides its inherent spectral convergence in accuracy,...
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In this paper, we present a stable, reliable and robust method for reconstructing a three dimensional density function from a set of two dimensional electron microscopy images. By minimizing an energy functional consi...
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In this paper, we present a stable, reliable and robust method for reconstructing a three dimensional density function from a set of two dimensional electron microscopy images. By minimizing an energy functional consisting of a fidelity term and a regularization term, a L 2 -gradient flow is derived. The flow is integrated by a finite element method in the spatial direction and an explicit Euler scheme in temporal direction. The experimental results show that the proposed method is efficient and effective.
We review the extended Jacobian approach to automatic differentiation of a user-supplied function and highlight the Schur complement form’s forward and reverse variants. We detail a Matlab operator overloaded approac...
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We review the extended Jacobian approach to automatic differentiation of a user-supplied function and highlight the Schur complement form’s forward and reverse variants. We detail a Matlab operator overloaded approach to construct the extended Jacobian that enables the function Jacobian to be computed using Matlab’s sparse matrix operations. Memory and runtime costs are reduced using a variant of the hoisting technique of Bischof (Issues in Parallel Automatic Differentiation, 1991). On five of the six mesh-based gradient test problems from The MINPACK2 Test Problem Collection (Averick et al, 1992) the reverse variant of our extended Jacobian technique with hoisting outperforms the sparse storage forward mode of the MAD package (Forth, ACM T. Math. Software. 32, 2006). For increasing problems size the ratio of gradient to function cpu time is seen to be bounded, if not decreasing, in line with Griewank and Walther’s (Evaluating Derivatives, SIAM, 2008) cheap gradient principle.
This article investigates how the Empirical Mode Decomposition (EMD) algorithm, a newly-developed and effective technique in the fields of signal processing and time-frequency analysis, is introduced and applied to ac...
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This article investigates how the Empirical Mode Decomposition (EMD) algorithm, a newly-developed and effective technique in the fields of signal processing and time-frequency analysis, is introduced and applied to activation detection in task-related functional Magnetic Resonance Imaging (fMRI) of the human brain. The method is illustrated using fMRI data simulated under one paradigm as well as one real dataset, and its performance is compared to those of a leading model based (General Linear Model ? GLM) and a leading data-driven (Region Growing Method ? RGM) approach. It is concluded that the proposed method achieves much better performance than the computationally inefficient RGM and is slightly more sensitive than GLM. Experimental results support its efficiency and sensitivity, which indicates that it is to become a viable alternative to the fMRI analysis.
Local mesh refinement is one of the key steps in the implementations of adaptive finite element methods. This paper presents a parallel algorithm for distributed memory parallel computers for adaptive local refinement...
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Local mesh refinement is one of the key steps in the implementations of adaptive finite element methods. This paper presents a parallel algorithm for distributed memory parallel computers for adaptive local refinement of tetrahedral meshes using bisection. This algorithm is used in PHG, Parallel Hierarchical Grid Chttp：//lsec. cc. ac. cn/phg/）, a toolbox under active development for parallel adaptive finite element solutions of partial differential equations. The algorithm proposed is characterized by allowing simukaneous refinement of submeshes to arbitrary levels before synchronization between submeshes and without the need of a central coordinator process for managing new vertices. Using the concept of canonical refinement, a simple proof of the independence of the resulting mesh on the mesh partitioning is given, which is useful in better understanding the behaviour of the biseetioning refinement procedure.
In this paper, determinant type solutions of the 2+1 dimensional Kaup‐Kuperschmidt (2DKK) equation are firstly obtained. Then the 2+1 dimensional Kaup‐Kuperschmidt equation with self‐consistent sources (2DKK ESCS) ...
In this paper, determinant type solutions of the 2+1 dimensional Kaup‐Kuperschmidt (2DKK) equation are firstly obtained. Then the 2+1 dimensional Kaup‐Kuperschmidt equation with self‐consistent sources (2DKK ESCS) is presented through the source generation procedure. Exact solutions of this coupled system are expressed in the terms of determinants. As examples, one and two‐soliton solutions are given.
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