PDE blending surfaces with C continuity

In this paper, we propose to use a general sixth-order partial differential equation (PDE) to solve the problem of C² continuous surface blending. Good accuracy and high efficiency are obtained by constructing a compound solution function, which is able to both satisfy the boundary conditions exactly and minimise the error of the PDE. This method can cope with much more complex surface-blending problems than other published analytical PDE methods. Comparison with the existing methods indicates that our method is capable of generating blending surfaces almost as fast and accurately as the closed-form method and it is more efficient and accurate than other extant PDE-based methods.     

Analytical solutions for sketch-based convolution surface modeling on the GPU

Convolution surfaces are attractive for modeling objects of complex evolving topology. This paper presents some novel analytical convolution solutions for planar polygon skeletons with both finite-support and infinite-support kernel functions. We convert the double integral over a planar polygon into a simple integral along the contour of the polygon based on Green’s theorem, which reduces the computational cost and allows for efficient parallel computation on the GPU. For finite support kernel functions, a skeleton clipping algorithm is presented to compute the valid skeletons. The analytical solutions are integrated into a prototype modeling system on the GPU (Graphics Processing Unit). Our modeling system supports point, polyline and planar polygon skeletons. Complex objects with arbitrary genus can be modeled easily in an interactive way. Resulting convolution surfaces with high quality are rendered with interactive ray casting.     

A curvature estimation for pen input segmentation in sketch-based modeling

A proper segmentation of pen marking enhances shape recognition and enables a natural interface for sketch-based modeling from simple line drawing tools to 3D solid modeling applications; user input is otherwise restricted to draw only one segment per one stroke. In general, the pen marking segmentation is achieved by detecting the points of high curvature-called, segmenting points-and splitting the pen marking at those points. This paper presents a curvature estimation method, which considers only local shape information. The proposed method can therefore estimate curvature on-the-fly while user is drawing on a pen-input display, such as tablet PCs.     

基于动态偏微分方程构造过渡面

为了实现交互式的偏微分方程曲面造型,针对传统静态偏微分方程构造过渡面存在的不足,提出了基于动态偏微分方程构造C1连续的过渡面,并引入迭代有限差分法求解偏微分方程的数值解,在此基础上构造了光滑过渡曲面.讨论了形状控制因子、密度、阻尼系数等物理参数的变化对曲面形状的影响,其中形状控制因子对生成曲面的形状影响最为明显.造型实例表明,利用动态偏微分方程构造过渡面具有更高的灵活性,大大提高了工业几何设计的交互性,在CAD/CAM中具有重要的应用价值.     

Algorithmic shape modeling with subdivision surfaces

We present methods for synthesizing 3D shape features on subdivision surfaces using multi-scale procedural techniques. Multi-scale synthesis is a powerful approach for creating surfaces with different levels of detail. Our methods can also blend multiple example multi-resolution surfaces, including procedurally defined surfaces as well as captured models.     

一种快速名片字符识别算法

针对嵌入式名片识别系统中低质名片字符特征提取困难导致识别速度慢和识别率低的问题,提出使用字符加权模板和基于统计的字符特征提取算法相结合,对提取的特征进行编码匹配.该算法对字符模板进行加权操作和网格化处理,并对每一块网格区域提取特征,并将提取出的特征在特征空间进行多尺度划分并采用二进制编码,这样用一串编码表示特征,最后通过编码匹配实现特征匹配.实验结果表明,该模板加权和特征提取方法与特征编码匹配结合可以较大地提高名片字符识别率.     

A new intrinsic numerical method for PDE on surfaces

In this note, we introduce a simple, effective numerical method, the local tangential lifting method, for solving partial differential equations for scalar- and vector-valued data defined on surfaces. Even though we follow the traditional way to approximate the regular surfaces under consideration by triangular meshes, the key idea of our algorithm is to develop an intrinsic and unified way to compute directly the partial derivatives of functions defined on triangular meshes. We present examples in computer graphics and image processing applications.     

Fast display of well-tesselated surfaces

Well-tesselated surfaces are piecewise planar functions on the sphere. Their planar faces are triangles which must meet a local geometric constraint. The faces may have arbitrary properties of transparency or reflectivity. These surfaces admit of simple hidden-line and -surface algorithms. In a raster graphics environment, the algorithms yield a priority ordering for painting entire faces. This order depends only upon the 3-D directions of face vertices as seen from the origin, and is independent of the radial position of vertices. Hence the order is independent of the actual function realized by the surface. Since perspective distortion and an approximate version of object rotation may both be accomplished by changing only radial vertex positions, these useful transformations may be visualized without resorting.Specific methods for creating well-tesselated surfaces are given, and general constraints defining them are stated. An efficient hidden surface/line algorithm is presented, with a simpler method for the case of opaque faced polyhedra. Proofs of correctness are provided.     

Statistical character structure modeling and its application to handwritten Chinese character recognition

This paper proposes a statistical character structure modeling method. It represents each stroke by the distribution of the feature points. The character structure is represented by the joint distribution of the component strokes. In the proposed model, the stroke relationship is effectively reflected by the statistical dependency. It can represent all kinds of stroke relationship effectively in a systematic way. Based on the character representation, a stroke neighbor selection method is also proposed. It measures the importance of a stroke relationship by the mutual information among the strokes. With such a measure, the important neighbor relationships are selected by the nth order probability approximation method. The neighbor selection algorithm reduces the complexity significantly because we can reflect only some important relationships instead of all existing relationships. The proposed character modeling method was applied to a handwritten Chinese character recognition system. Applying a model-driven stroke extraction algorithm that cooperates with a selective matching algorithm, the proposed system is better than conventional structural recognition systems in analyzing degraded images. The effectiveness of the proposed methods was visualized by the experiments. The proposed method successfully detected and reflected the stroke relationships that seemed intuitively important. The overall recognition rate was 98.45 percent, which confirms the effectiveness of the proposed methods.     

Fast self-generation voting for handwritten Chinese character recognition

In this paper, a fast self-generation voting method is proposed for further improving the performance in handwritten Chinese character recognition. In this method, firstly, a set of samples are generated by the proposed fast self-generation method, and then these samples are classified by the baseline classifier, and the final recognition result is determined by voting from these classification results. Two methods that are normalization-cooperated feature extraction strategy and an approximated line density are used for speeding up the self-generation method. We evaluate the proposed method on the CASIA and CASIA-HWDB1.1 databases. High recognition rate of 98.84 % on the CASIA database and 91.17 % on the CASIA-HWDB1.1 database are obtained. These results demonstrate that the proposed method outperforms the state-of-the-art methods and is useful for practical applications.     

Markov random field-based statistical character structure modeling for handwritten Chinese character recognition

This paper proposes a statistical-structural character modeling method based on Markov random fields (MRFs) for handwritten Chinese character recognition (HCCR). The stroke relationships of a Chinese character reflect its structure, which can be statistically represented by the neighborhood system and clique potentials within the MRF framework. Based on the prior knowledge of character structures, we design the neighborhood system that accounts for the most important stroke relationships. We penalize the structurally mismatched stroke relationships with MRFs using the prior clique potentials, and derive the likelihood clique potentials from Gaussian mixture models, which encode the large variations of stroke relationships statistically. In the proposed HCCR system, we use the single-site likelihood clique potentials to extract many candidate strokes from character images, and use the pairsite clique potentials to determine the best structural match between the input candidate strokes and the MRF-based character models by relaxation labeling. The experiments on the KAIST character database demonstrate that MRFs can statistically model character structures, and work well in the HCCR system.     

Fast on-line signature recognition based on VQ with time modeling

This paper proposes a multi-section vector quantization approach for on-line signature recognition. We have used the MCYT database, which consists of 330 users and 25 skilled forgeries per person performed by 5 different impostors. This database is larger than those typically used in the literature. Nevertheless, we also provide results from the SVC database.Our proposed system outperforms the winner of SVC with a reduced computational requirement, which is around 47 times lower than DTW. In addition, our system improves the database storage requirements due to vector compression, and is more privacy-friendly as it is not possible to recover the original signature using the codebooks. Experimental results with MCYT provide a 99.76% identification rate and 2.46% EER (skilled forgeries and individual threshold). Experimental results with SVC are 100% of identification rate and 0% (individual threshold) and 0.31% (general threshold) when using a two-section VQ approach.     

Fast variational design of multiresolution curves and surfaces with B-spline wavelets

Multiresolution modeling provides a powerful tool for complex shape editing. To achieve a better control of deformations and a more intuitive interface, variational principles have been used in such multiresolution models. However, when handling multiresolution constraints, the existing methods often result in solving large optimization systems. Hence, the computational time may become too excessive to satisfy the requirements for interactive design in CAD. In this paper, we present a fast approach for interactive variational design of multiresolution models. By converting all constraints at different levels to a target level, the optimization problem is formulated and solved at the lower level. Thus, the unknown coefficients of the optimization system are significantly reduced. This improves the efficiency of variational design. Meanwhile, to avoid smoothing out the details of the shape in variational modeling, we optimize the change in the deformation energy instead of the total energy of the deformed shape. Several examples and the experimental results are given to demonstrate the effectiveness and efficiency of this approach.     

Fast adaptive blue noise on polygonal surfaces

This paper proposes a novel method for the computation of hierarchical Poisson disk samplings on polygonal surfaces. The algorithm generates a pointerless hierarchical structure such that each level is a uniform Poisson disk sampling and a subset of the next level. As the main result, given a dynamically-varying importance sampling function defined over a surface, the hierarchy is capable of generating adaptive samplings with blue noise characteristics, temporal-coherence and real-time computation. Classical algorithms produce hierarchies in tight ratios, which is a serious bottleneck specially for a large number of samples. Instead, our method uses sparse ratios and decreases the adaptation error of the hierarchy through a fast optimization process. Therefore, we save a considerable amount of time (up to 74% in our experiments) while preserving the good blue noise properties. We present applications on Non-Photo Realistic rendering (NPR), more specifically, on surface stippling effects. First, we apply our method by taking illumination to be the importance sampling to shade the surface, and second, we dynamically deform a surface with a predefined stippled texture.     

基于卷积曲面的几何造型方法

卷积曲面是一种很有潜力的隐式曲面造型方法。由于卷积的可叠加性质,使得其生成的曲面很光滑,不会产生凸包和裂缝。卷积曲面造型是基于骨架的,其骨架可以是曲线或曲面,也可以以物体轮廓线为骨架原型来获取所需要的物体造型。在卷积造型的过程中,通过对骨架加权可以精细地控制结果曲面的形状。在介绍了卷积曲面造型的各类方法后,分析了其特点和发展方向。     

Combining CSG modeling with soft blending using Lipschitz-based implicit surfaces

In this paper a general method is given for combining CSG modeling with soft blending using implicit surfaces. A class of various blending functions sharing some desirable properties like differentiability and intuitive blend control are given. The functions defining the CSG objects satisfy the Lipschitz condition that gives the possibility of fast root finding but can also prove useful in the field of collision detection and adaptive triangulation.