激光三维扫描数据的表面重建

对激光三维扫描系统获得的没有任何附加信息的轮廓线点云数据进行处理,首先采用求最大连通域的方法删除噪声点,利用设定相邻点连线夹角正切阈值的方法精简数据,然后采用基于局部切平面簇的方法对数据点云进行切平面的估算、法向量的调整和计算距离函数,用改进的MC方法输出三维网格,并且应用基于顶点的网格删除算法对三维网格进行简化,在估算切平面的时候采用新的估算原则,提高了重建速度,改善了重建效果,所表述的重建流程,成功地解决了激光扫描系统所得轮廓数据点的表面重建问题。     

三维表面模型的快速切割算法

讨论了一个三维表面模型的快速切割算法.由改进的MC(marching cubes)方法抽取、构成了连续曲面的分组信息以及构成曲面的三角面片的层次包围盒信息，并利用记录了上述信息的B+树模型,完成了三维表面模型的快速切割算法.讨论的算法通过充分发掘和利用MC算法中所隐含的三角面片的包围盒信息和物体各部分间的三维相关信息，在对三维表面模型进行切割计算时,可以快速定位交点，并且根据交点信息，不必遍历模型的所有三角面片，而直接完成对整个被切割模型的分割.研究背景是髋关节整型手术中平面手术刀及球面手术刀对髋关节的切     

利用VTK进行三维肠道重建算法的改进

肠道CT的三维重建是提高肠道疾病诊疗准确性的迫切需要。利用可视化工具包VTK并结合VC++,实现了肠道三维重建。经典三维重建Marching Cubes（简称MC）算法会产生二义性,针对常用的渐近线法消除二义性计算量大的问题,提出了一种改进的MC算法：采用线性插值法求出二义性面与等值面的交点,然后分别连接二义性面对边上的交点形成两条相交直线,最后通过判断直线交点的状态值,来唯一地确定等值线的连接方式,从而快速重建出三维肠道。实验结果表明,利用改进的MC算法比起传统MC算法,在三维重建的质量和效率上都得到了很大的提高。     

Adaptive marching cubes

The marching cubes algorithm (MC) is a powerful technique for surface rendering that can produce very high-quality images. However, it is not suitable for interactive manipulation of the 3D surfaces constructed from high-resolution volume datasets in terms of both space and time. In this paper, we present an adaptive version of MC called adaptive marching cubes (AMC). It significantly reduces the number of triangles representing the surface by adapting the size of the triangles to the shape of the surface. This improves the performance of the manipulation of the 3D surfaces. A typical example with the volume dataset of size 256×256×113 shows that the number of triangles is reduced by 55%. The quality of images produced by AMC is similar to that of MC. One of the fundamental problems encountered with adaptive algorithms is thecrack problem. Cracks may be created between two neighboring cubes processed with different levels of subdivision. We solve the crack problem by patching the cracks using polygons of the smae shape as those of the cracks. We propose a simple, but complete, method by first abstracting 22 basic configurations of arbitrarily sized cracks and then reducing the handling of these configurations to a simple rule. It requires onlyO(n ²) working memory for an×n×n volume data set.     

High‐speed Marching Cubes using HistoPyramids

We present an implementation approach for Marching Cubes (MC) on graphics hardware for OpenGL 2.0 or comparable graphics APIs. It currently outperforms all other known graphics processing units (GPU)‐based iso‐surface extraction algorithms in direct rendering for sparse or large volumes, even those using the recently introduced geometry shader (GS) capabilites. To achieve this, we outfit the Histogram Pyramid (HP) algorithm, previously only used in GPU data compaction, with the capability for arbitrary data expansion. After reformulation of MC as a data compaction and expansion process, the HP algorithm becomes the core of a highly efficient and interactive MC implementation. For graphics hardware lacking GSs, such as mobile GPUs, the concept of HP data expansion is easily generalized, opening new application domains in mobile visual computing. Further, to serve recent developments, we present how the HP can be implemented in the parallel programming language CUDA (compute unified device architecture), by using a novel 1D chunk/layer construction.     

基于锥束CT的两类三维表面重构方法比较研究

目前锥束CT的三维重构主要采用面绘制,其方法有两类,即体素级重构和切片级重构。在对比两类方法的基础上,提出了一种新的二维切片轮廓重构与三维表面重构相结合的切片级重构方法,然后以标准MC算法和该算法分别对两个实例进行重构并比较。结果表明,该算法更适合工业产品的三维表面重构。     

基于MC的医学三维等值面的平滑与归并

为了提高医学三维图象的重建效果和速度,在对用于构造等值面的MC（Marching Cubes）算法进行分析的基础上,提出了对等值面进行三维空间方向平滑和多边形法形法向归并的方法。等值面方向平滑的方法就是将等值面分解为一个三维坐标场和一个法向矢量场,然后对其法向矢量场作矢量平滑处理;而等值面的多边形法向归并则是根据适当的门限值,将原来由大量小三角面片构成的等值面归并成由较少的多边形面片构成的等值面。实验结果表明,该方法能显著改善三维重建的效果,并能提高三维绘制的速度。     

A parallelized surface extraction algorithm for large binary image data sets based on an adaptive 3D delaunay subdivision strategy

In this paper we describe a novel 3D subdivision strategy to extract the surface of binary image data. This iterative approach generates a series of surface meshes that capture different levels of detail of the underlying structure. At the highest level of detail, the resulting surface mesh generated by our approach uses only about 10% of the triangles in comparison to the marching cube algorithm (MC) even in settings were almost no image noise is present. Our approach also eliminates the so-called "staircase effect" which voxel based algorithms like the MC are likely to show, particularly if non-uniformly sampled images are processed. Finally, we show how the presented algorithm can be parallelized by subdividing 3D image space into rectilinear blocks of subimages. As the algorithm scales very well with an increasing number of processors in a multi-threaded setting, this approach is suited to process large image data sets of several gigabytes. Although the presented work is still computationally more expensive than simple voxel-based algorithms, it produces fewer surface triangles while capturing the same level of detail, is more robust towards image noise and eliminates the above-mentioned "staircase" effect in anisotropic settings. These properties make it particularly useful for biomedical applications, where these conditions are often encountered.     

Solving constrained Markovian evolution in QCD with the help of the non-Markovian Monte Carlo

We present the constrained Monte Carlo (CMC) algorithm for the QCD evolution. The constraint resides in that the total longitudinal energy of the emissions in the MC and in the underlying QCD evolution is predefined (constrained). This CMC implements exactly the full DGLAP evolution of the parton distributions in the hadron with respect to the logarithm of the energy scale. The algorithm of the CMC is referred to as the non-Markovian type. The non-Markovian MC algorithm is defined as the one in which the multiplicity of emissions is chosen randomly as the first variable and not the last one, as in the Markovian MC algorithms. The former case resembles that of the fixed-order matrix element calculations. The CMC algorithm can serve as an alternative to the so-called backward evolution Markovian algorithm of Sjöstrand, which is used for modeling the initial-state parton shower in modern QCD MC event generators. We test practical feasibility and efficiency of our CMC implementation in a series of numerical exercises, comparing its results with those from other MC and non-MC programs, in a wide range of Q and x, down to the 0.1% precision level. In particular, satisfactory numerical agreement is found with the results of the Markovian MC program of our own and the other non-MC program. The efficiency of the new constrained MC is found to be quite good.     

三维模型有向三角面片链码压缩方法

首先提出一种适用于三角面片链码算法的改进MC规格化方法,使用单位为2的体素作为改进MC算法中的单位体素,并使用其中的27个顶点重新构建等值面,最终获取高质量的规格化三角网格模型.在新的规格化模型上提出一种新的面片遍历方式,在三角面片链码算法的基础上,采用优先遍历右连接面片原则,控制面片的遍历方向,该方法能够减少面片遍历...     

工业CT数据场面绘制和体绘制改进算法研究

工业CT图像的重建速度和精度是工业CT产品的两个重要指标。针对面绘制的MC算法提出了一种基于相似性区域分割的三维工业图像表面重建算法,实现了准确分割,并利用分割结果精确地提取等值面,显著提高了检测效率;针对体绘制的光线投射算法提出了一种基于二维最大熵阈值的分割预处理方法,利用二维直方图熵最大化寻找阈值的最佳组合,能有效减少重建体数据量,实测数据表明体绘制速度明显提高。     

Curve skeleton extraction by coupled graph contraction and surface clustering

In this paper, we present a practical algorithm to extract a curve skeleton of a 3D shape. The core of our algorithm comprises coupled processes of graph contraction and surface clustering. Given a 3D shape represented by a triangular mesh, we first construct an initial skeleton graph by directly copying the connectivity and geometry information from the input mesh. Graph contraction and surface clustering are then performed iteratively. The former merges certain graph nodes based on computation of an approximate centroidal Voronoi diagram, seeded by subsampling the graph nodes from the previous iteration. Meanwhile, a coupled surface clustering process serves to regularize the graph contraction. Constraints are used to ensure that extremities of the graph are not shortened undesirably, to ensure that skeleton has the correct topological structure, and that surface clustering leads to an approximately-centered skeleton of the input shape. These properties lead to a stable and reliable skeleton graph construction algorithm.Experiments demonstrate that our skeleton extraction algorithm satisfies various desirable criteria. Firstly, it produces a skeleton homotopic with the input (the genus of both shapes agree) which is both robust (results are stable with respect to noise and remeshing of the input shape) and reliable (every boundary point is visible from at least one curve-skeleton location). It can also handle point cloud data if we first build an initial skeleton graph based on k-nearest neighbors. In addition, a secondary output of our algorithm is a skeleton-to-surface mapping, which can e.g. be used directly for skinning animation.Highlights(1) An algorithm for curve skeleton extraction from 3D shapes based on coupled graph contraction and surface clustering. (2) The algorithm meets various desirable criteria and can be extended to work for incomplete point clouds.     

Geometric fusion for a hand-held 3D sensor

Abstract. This article presents a geometric fusion algorithm developed for the reconstruction of 3D surface models from hand-held sensor data. Hand-held systems allow full 3D movement of the sensor to capture the shape of complex objects. Techniques previously developed for reconstruction from conventional 2.5D range image data cannot be applied to hand-held sensor data. A geometric fusion algorithm is introduced to integrate the measured 3D points from a hand-held sensor into a single continuous surface. The new geometric fusion algorithm is based on the normal-volume representation of a triangle, which enables incremental transformation of an arbitrary mesh into an implicit volumetric field function. This system is demonstrated for reconstruction of surface models from both hand-held sensor data and conventional 2.5D range images. Received: 30 August 1999 / Accepted: 21 January 2000     

Constrained MC for QCD evolution with rapidity ordering and minimum kT

With the imminent start of LHC experiments, development of phenomenological tools, and in particular the Monte Carlo programs and algorithms, becomes urgent. A new algorithm for the generation of a parton shower initiated by the single initial hadron beam is presented. The new algorithm is of the class of the so-called “constrained MC” type algorithm (an alternative to the backward evolution MC algorithm), in which the energy and the type of the parton at the end of the parton shower are constrained (predefined). The complete kinematics configurations with explicitly constructed four momenta are generated and tested. Evolution time is identical with rapidity and minimum transverse momentum is used as an infrared cut-off. All terms of the leading-logarithmic approximation in the DGLAP evolution are properly accounted for. In addition, the essential improvements towards the so-called CCFM/BFKL models are also properly implemented. The resulting parton distributions are cross-checked up to the 10⁻³ precision level with the help of a multitude of comparisons with other MC and non-MC programs. We regard these tests as an important asset to be exploited at the time when the presented MC will enter as a building block in a larger MC program for W/Z production process at LHC.     

医学图像中微细管道结构的表面绘制算法

在医学图像处理中,常常需要提取出特定的组织或者结构,再以提取到的二值体数据为基础,对组织结构进行三维重建。传统的Marching Cube（MC）算法在对微细结构进行三维重建时,可能会产生断裂现象,不能有效保持原始体数据的连通性。以血管体数据为例,针对医学图像中微细管道结构重建提出一种改进的MC算法,以保持重建后组织结构的连通性。     

Reconstruction of consistent shape from inconsistent data: Optimization of 2{\raise0.5ex\hbox{D sketches

Although the 3D orientations of edges and surfaces are theoretically sufficient for reconstructing the 3D object shape, this does not mean that the 3D object shape can actually be reconstructed. Specifying the edge and surface orientations is often overspecification, and inconsistency may result if image data contain errors. We propose a scheme of optimization to construct a consistent polyhedron shape from inconsistent data. Our optimization is achieved by solving a set of linear equations; no searchers and iterations are necessary. This technique is first applied to the problem of shape-from-motion and then to the 3D recovery based on the rectangularity hypothesis and the parallelism hypothesis. We also present a strategy of heuristic reasoning on rectangularity and parallelism.     

Interactive 3D video editing

We present a generic and versatile framework for interactive editing of 3D video footage. Our framework combines the advantages of conventional 2D video editing with the power of more advanced, depth-enhanced 3D video streams. Our editor takes 3D video as input and writes both 2D or 3D video formats as output. Its underlying core data structure is a novel 4D spatio-temporal representation which we call the video hypervolume. Conceptually, the processing loop comprises three fundamental operators: slicing, selection, and editing. The slicing operator allows users to visualize arbitrary hyperslices from the 4D data set. The selection operator labels subsets of the footage for spatio-temporal editing. This operator includes a 4D graph-cut based algorithm for object selection. The actual editing operators include cut & paste, affine transformations, and compositing with other media, such as images and 2D video. For high-quality rendering, we employ EWA splatting with view-dependent texturing and boundary matting. We demonstrate the applicability of our methods to post-production of 3D video.     

基于分割的三维医学图像表面重建算法

提出了一种基于分割的三维医学图像表面重建算法,它将图像分割与MC(marching cubes)算法有机地结合,这样可以根据不同医学图像的特点,采用适合的分割方法,实现对不同组织的准确分割,并利用分割结果精确地提取等值面,避免了MC只适合于阈值分割的局限性.同时采用一种基于区域增长的立方体检测方法,提高了表面跟踪的效率.实验证明,运用本算法,重建速度和显示效果均有提高.     

Photo Hull regularized stereo

A regularization-based approach to 3D reconstruction from multiple images is proposed. As one of the most widely used multiple-view 3D reconstruction algorithms, Space Carving can produce a Photo Hull of a scene, which is at best a coarse volumetric model. The two-view stereo algorithm, on the other hand, can generate a more accurate reconstruction of the surfaces, provided that a given surface is visible to both views. The proposed method is essentially a data fusion approach to 3D reconstruction, combining the above two algorithms by means of regularization. The process is divided into two steps: (1) computing the Photo Hull from multiple calibrated images and (2) selecting two of the images as input and solving the two-view stereo problem by global optimization, using the Photo Hull as the regularizer. Our dynamic programming implementation of this regularization-based stereo approach potentially provides an efficient and robust way of reconstructing 3D surfaces. The results of an implementation of this theory is presented on real data sets and compared with peer algorithms.