Complete 3D surface reconstruction from unstructured point cloud

In this study, a complete 3D surface reconstruction method is proposed based on the concept that the vertices of surface model can be completely matched to the unstructured point cloud. In order to generate the initial mesh model from the point cloud, the mesh subdivision of bounding box and shrink-wrapping algorithm are introduced. The control mesh model for well representing the topology of point cloud is derived from the initial mesh model by using the mesh simplification technique based on the original QEM algorithm, and the parametric surface model for approximately representing the geometry of point cloud is derived by applying the local subdivision surface fitting scheme on the control mesh model. And, to reconstruct the complete matching surface model, the insertion of isolated points on the parametric surface model and the mesh optimization are carried out. Especially, the fast 3D surface reconstruction is realized by introducing the voxel-based nearest-point search algorithm, and the simulation results reveal the availability of the proposed surface reconstruction method.     

曲面重构中散乱点云数据曲率估算算法的研究

获取测量点云数据的几何特征信息是曲面重构的基础,估算数据点方向矢量和曲率是点云数据处理中必须面对的问题。这里针对散乱测量数据点云,以局部数据点协方差矩的最小特征向量作为数据点的方向矢量,并根据实际测量情况,对基于二次曲面拟合的数据点曲率估算算法进行了改进。对实际测量点云数据,能够较准确地估算出点云方向矢量和曲率,并能形象显示出数据点云的曲率分布。     

散乱数据点的齿面重建及局部特征优化

为了建立齿轮修形技术中拓扑修形且包含特征的精确数字化齿面,提出一种对大量散乱数据点根据给定的精度重建出包含详细特征且满足精度的细分齿面算法。该算法以齿面上的大量散乱点数据为输入量,通过对其进行预处理,采用螺旋增长算法构造出具有一定逼近程度的初始网格,对初始网格进行带有特征的Loop细分,根据给定精度估计出满足精度需要的最少细分次数,每次细分后反复交叉调整细分点,使重建齿面不断逼近实际齿面。通过重建后的齿面与实际齿面误差分析的实例,证明了算法的可行性与准确性。     

基于分层块状全局搜索的三维点云自动配准

提出了一种分层块状全局搜索到临近点局部搜索的改进迭代最近点(ICP)算法,用于进一步提高ICP算法的配准速度并消除点云缺失对点云配准的影响。该配准方法在粗略配准之后,以点云块为分层单元对模型点集进行选取,并对选取的少量模型点进行全局搜索获取其对应最近点;然后,以这些模型点对应的最近点作为搜索中心,在场景点集中进行局部搜索,获取这些模型点的大量临近点的对应最近点;最后,剔除错误对应最近点对,并求取坐标变换。与基于KD-Tree的ICP算法和基于LS+HS(Logarithmic Search Combined with Hierarchical Model Point Selection )的ICP算法相比,该配准算法对Happy bunny扫描数据的配准速度分别提高了78%和24%;对Dragon扫描数据的配准速度分别提高了73%和30%。这些结果表明该算法可以快速、精确地实现三维点云间的配准。     

车身外覆盖件设计中点云重构A级曲面技术

A级曲面重构是车身外覆盖件设计的关键环节,针对传统方法重构复杂自由曲面效率低下、灵活性差、曲面质量不高的状况,提出一种基于NURBS面片的A级曲面重构方法,曲面调整灵活、直观,有效提高了A级曲面重构的效率和质量.     

基于激光扫描和SFM的非同步点云三维重构方法

室外场景具有测量数据量大、扫描数据易重叠及建筑物表面信息复杂等特点,单靠激光扫描方法能够获得场景精确的深度信息,但缺乏颜色和纹理信息,利用从运动中恢复结构(SFM)方法可获得丰富的彩色信息,但重构精度不高,若将两种设备固定进行在线实时同步测量,易受到测量环境和系统制约不易实现。针对此问题,提出了一种基于激光扫描和SFM结合的非同步点云数据融合的三维重构方法。首先,提出利用手动选择控制点进行7自由度初始配准,再利用迭代最近点(ICP)算法对初始配准结果进行精确配准,最后利用最近点搜索算法将分布在经基于面片的多视图立体视觉(PMVS)算法优化后的SFM数据中的颜色信息与激光扫描的点云坐标进行融合。实验结果和数据分析显示,本文的方法能有效地将激光扫描与SFM点云数据进行融合,实现了室外大场景的三维彩色重构。     

An adaptive mesh model for 3D reconstruction from unorganized data points

Reconstructing exact topology mesh from data points is one of the most important tasks in the fields of industrial CAD/CAE/CAM, computational vision and reverse engineering. In this paper, a deflation algorithm that integrates an adaptive mesh and physical constraint model is presented for the 3D reconstruction of geometric-closed shape (genus 0) from unorganized data points. First, an initial mesh is formed using the Delaunay algorithm. Second, an asymptotic deforming performance is accomplished to deflate initial mesh towards the local concave boundary step-by-step. In this phase, a physical constraint model of coupled particle systems based on particle dynamics and Newtonian law of motion is constructed, and the model dynamically controls mesh deformation as a behavior constraint. To guarantee that the resultant mesh is homeomorphous to the original surface of data points, a continuously deforming mechanism, visibility cone and collision-detecting criterions are designed. At last, experimental results in reverse engineering which supports the usefulness of this method for reconstruction .     

基于CGAL的点云三角面片重构

点云的三角面片重构是曲面重构的基础,通过三角面片重构可得到离散点的邻接关系,这些邻接关系为曲面拟合提供必要的信息.介绍了一个功能强大的计算几何库CGAL,并利用它完成对面模型的点云三角面片重构和体模型的点云三角面片重构.     

Rapid surface reconstruction from a point cloud using the least-squares projection

A new approach for the rapid and robust surface reconstruction from a point cloud is presented based on the distance field and the least-squares projection (LSP) algorithm. This novel approach works directly on the point cloud without any explicit or implicit surface reconstruction procedure. First, a coarse base polygonal model was created directly from the distance field for the given point cloud through the iso-surface extraction. After acquiring a rough base polygonal model, we obtain a quality polygonal model through the iterative refinement and least-squares projection which projects current working polygonal model onto the point cloud in a least-squares sense. The main contribution of this work is the robust and fast surface reconstruction from randomly scattered 3D points only without any further information. We demonstrate the validity and efficiency of this new approach through a number of application examples.     

SFS三维重构技术的发展现状与趋势研究

从明暗恢复形状(SFS)是计算机视觉中三维重构问题的关键技术之一,其原理是利用单幅图像的明暗变化来恢复物体表面的三维形状,应用领域十分广泛.介绍了近些年来SFS方法的发展现状,将SFS算法划分为四种类型:演化和偏微分方程(PDE)方法、最优化方法、局部化方法以及线性化方法.同时,分析了各种SFS算法的特点,并对SFS技...