黄 劲 贵定 一中 浙江大学 计算机 图形学 Jin Huang Jin_Huang2.jpg I am an Assistant Professor/Postdortoral in College of Computer Science at Zhejiang University. My advisor is Prof. Hujun Bao in the Computer Graphics Group at State Key Lab of CAD&CG. I'm working in the area of computer graphics. Current interests are mainly in geometry processing and physically based deformable object simulation. hj AT cad.zju.edu.cn

State Key Lab of CAD&CG, Zijingang Campus, Zhejiang University, Hangzhou, 310058, P.R.China

We present a novel technique for large deformations on 3D meshes using the volumetric graph Laplacian. We first construct a graph representing the volume inside the input mesh. The graph need not form a solid meshing of the input mesh's interior; its edges simply connect nearby points in the volume. This graph's Laplacian encodes volumetric details as the difference between each point in the graph and the average of its neighbors. Preserving these volumetric details during deformation imposes a volumetric constraint that prevents unnatural changes in volume. We also include in the graph points a short distance outside the mesh to avoid local self-intersections. Volumetric detail preservation is represented by a quadric energy function. Minimizing it preserves details in a least-squares sense, distributing error uniformly over the whole deformed mesh. It can also be combined with conventional constraints involving surface positions, details or smoothness, and efficiently minimized by solving a sparse linear system.We apply this technique in a 2D curve-based deformation system allowing novice users to create pleasing deformations with little effort. A novel application of this system is to apply nonrigid and exaggerated deformations of 2D cartoon characters to 3D meshes. We demonstrate our system's potential with several examples. Point sets have become a popular shape representation. In this paper, we present a novel approach to computing variation modes for point set surfaces, and represent the point set surface as a linear combination of the variation modes, called a generative representation for the point set surface. Given a point set, our approach consists of two steps: The first is to produce a set of new samples with increasing smoothness and less detailed features. We use a modified smoothing method based on moving least squares (MLS) surface to produce the samples. The second is to arrange the shape vectors of the new samples together with the original point set into a matrix, and then compute the singular value decomposition of the matrix, producing a set of variation modes (the eigen vectors). Using the variation modes and the generative representation, we can easily synthesize new shapes. Typical applications are low/high/band pass filtering as well as denoising and detail enhancement in multiple scales. We present a fast deformation method for flexible objects. The deformation of the object is physically modeled using a linear elasticity model with a displacement based finite elements method, yielding a linear system at each time step of simulation. We solve this linear system using a precomputed force-displacement matrix, which describes the object response in terms of displacement accelerations to the forces acting on each vertex. We exploit the spatial coherence to effectively compress the force-displacement matrix to make this method practical and efficient by applying the clustered principal component analysis method. And we developed a method to efficiently handle the additional constraints for interactive user manipulation. At last large deformations are addressed based upon the compressed force-displacement matrix by combining a domain decomposition method and tracking the rotational motions. The experimental results demonstrate fast performances on complex large scale objects under interactive user manipulations. Efficiently simulating large deformations of flexible objects is a challenging problem in computer graphics. In this paper, we present a physically based approach to this problem, using the linear elasticity model and a finite elements method. To handle large deformations in the linear elasticity model, we exploit the domain decomposition method, based on the observation that each sub-domain undergoes a relatively small local deformation, involving a global rigid transformation. In order to efficiently solve the deformation at each simulation time step, we pre-compute the object responses in terms of displacement accelerations to the forces acting on each node, yielding a force-displacement matrix. However, the force-displacement matrix could be too large to handle for densely tessellated objects. To address this problem, we present two methods. The first method exploits spatial coherence to compress the force-displacement matrix using the clustered principal component analysis method; and the second method pre-computes only the force-displacement vectors for the boundary vertices of the sub-domains and resorts to the Cholesky factorization to solve the acceleration for the internal vertices of the sub-domains. Finally, we present some experimental results to show the large deformation effects and fast performance on complex large scale objects under interactive user manipulations. 提出一种基于实例的非真实感图像绘制算法.该算法利用两种纹理合成的基本方法,通过参数调整控制匹配点在结构与细节间的倾向性,把输入样图中的绘画风格传输到目标图片中,实现了自动绘画功能.另外,还提出一种搜索算法,该算法可以大大地加快纹理合成速度.实验证明文中算法十分有效.