无序图像三维重构中的图像选择技术

针对无序图像的三维重构问题,本文提出了一种图像选择算法,在三维重构算法运行之前,首先利用图像间的全局运动估计,去除冗余的图像,有效的减少了问题的规模,同时保持图像间的大部分连接关系,并能够较好地防止出现退化情况。为了验证本文的算法,针对一系列图像进行了测试,实验结果证明,作为三维重构的一个预处理过程,提高了三维重构算法的运行效率和算法的鲁棒性,具有很高的实用价值。     

三维散乱点云快速曲面重建算法

提出了一种基于Delaunay三角剖分的三维散乱点云快速曲面重建算法。算法首先计算点云的Delaunay三角剖分, 从Delaunay四面体提取初始三角网格, 根据Voronoi体元的特征构造优先队列并生成种子三角网格, 然后通过区域生长的方式进行流形提取。实验结果表明, 该算法可以高效、稳定地重构具有复杂拓扑结构、非封闭曲面甚至是非均匀采样的点云数据。与传统的基于Delaunay的方法比较, 该算法仅需要进行一次Delaunay三角剖分, 无须极点的计算, 因此算法的重构速度快。     

三维物体表面重建的分支处理算法研究

根据平面点集Delaunay三角剖分的特性,将Delaunay三角剖分应用到分支问题上,改进和实现了一种分支问题处理算法。将相邻层轮廓线投影到同一个剖面上形成一个带约束边的平面点集,并将它们Delaunay三角化,根据这些三角形组来生成新的轮廓线,使轮廓线一一对应。实验结果表明该算法实现的效果较符合实际情况,能有效地处理各种不同情况。     

基于Delaunay剖分的心内膜表面动态三维重建算法

心内膜表面三维重建技术在三维标测系统起着手术导航和靶点定位的作用。针对心内科手术中实时采集的散乱心内膜点云,提出了一种基于Delaunay剖分的表面动态三维重建算法。以CGAL非递归方式实现的逐点插入计算Delaunay剖分算法为基础,在剖分过程中,用关联采样点的伞局部替换原来表面中不满足Gabriel准则表面面片的集合,心内膜表面结构随着点云Delaunay剖分的变化而进行动态地更新。同时为了有效地表达心内膜表面及其点云的Delaunay剖分,并能够快速地索引四面体网格和表面三角面片,提出了一种以vtkDataArray为基础的几何数据结构。最后,实验表明该方法在重建结果和重建时间上可以满足心内科手术中的临床应用。     

Bayesian 3D shape from silhouettes

This paper introduces a smooth posterior density function for inferring shapes from silhouettes. Both the likelihood and the prior are modelled using kernel density functions and optimisation is performed using gradient ascent algorithms. Adding a prior allows for the recovery of concave areas of the shape that are usually lost when estimating the visual hull. This framework is also extended to use colour information when it is available in addition to the silhouettes. In these cases, the modelling not only allows for the shape to be recovered but also its colour information. Our new algorithms are assessed by reconstructing 2D shapes from 1D silhouettes and 3D faces from 2D silhouettes. Experimental results show that using the prior can assist in reconstructing concave areas and also illustrate the benefits of using colour information even when only small numbers of silhouettes are available.     

多轮廓线的三维形体重构技术研究与实现

实际应用中,三维重构经常面对的不是直接的体数据信息,而是一序列的二维轮廓线数据,因此基于轮廓线的三维重构研究有着极其重要的实用价值。在多轮廓线的三维形体重构中,轮廓对应、轮廓拼接、分叉处理和末端轮廓线的封闭处理等是其关键技术。提出了三维重构中每一个实现步骤具体的解决方案。针对轮廓线绕向问题提出了夹角和检测法,有效避免了轮廓多边形的绕向误判;对轮廓线一对多分叉问题提出了按周长比率解决问题的思路;在末端轮廓线的三角剖分算法中提出了最大张角三角形方法,减少了三角剖分的计算量,达到了在各种形态轮廓线条件下能够实现正确的拼接。实现结果表明,轮廓线拼接过程中每个步骤的解决方法是正确有效的,相较于其他实现方法通用性更强。     

用单数码相机实现物体表面的三维重建

根据由运动重建物体结构的原理,设计了一个简便易操作的三维重建系统,具体做法是:先用张氏标定法求得内参数矩阵,然后在两个不同的未知位置拍摄物体得到两幅图像,经立体匹配后,利用图像特征点的对应关系求解基本矩阵和本质矩阵,分解本质矩阵获得两个拍摄位置确定的摄像机运动参数(旋转矩阵和平移向量),进而求出相机在两个位置的投影矩阵,最后用三角法计算出物体表面特征点的三维坐标并在OpenGL中重建物体表面.和传统的立体视觉系统相比,本系统只需要一台数码相机和平面方格模板就可以实现三维重建,因此适用于普通相机用户.     

基于双视角的真实感三维人脸重建系统

人脸建模是计算机图形学及三维重建领域的一个研究热点,论文根据结构 光测量及编码原理,利用两组CCD 及结构光投影仪实现了人脸双视角测量,保证了数据测 量的范围和完整性;针对测量得到的几何及纹理数据,开发了可视化数据软件处理平台,能 够完成两部分数据的精简、分割、拼接及网格化等处理过程,并通过纹理映射实现具有真实 感的人脸模型三维重建;最终,将上述硬件测量方案及软件处理平台结合,形成了一套完整 的三维人脸重建系统,并通过试验验证了系统的可行性。     

基于侧影轮廓的三维模型快速重建

提出一种基于侧影轮廓进行三维模型重建的新方法,将传统的三维锥形交叉问题转换成二维轮廓交叉问题。首先,将不同视角下的二维侧影轮廓反投影到若干个平行的三维平面上,然后在三维平面上计算所有反投影轮廓的交叉轮廓,最后对相邻三维平面上的交叉轮廓进行匹配并重建物体的表面。理论分析和实验结果表明该算法的时间复杂度和视角数目呈线性关系。由于该方法主要以增加视角数目来提高模型的精确度,所以比三维锥形交叉的方法能更快速地重建物体精确的三维模型。     

基于Direct3D的海底地形显示方法研究

海底地形是海洋环境的主要组成部分,在军事及海洋开发领域具有重要价值。因而本文提出了基于规则网格的三角网生长法构造不规则三角网,并通过不规则三角网搭建海底地形的思路,在Direct3D环境下进行了仿真,生成的海底地形具有较高的真实感,能够逼真地反映出海底复杂的地形环境     

三维约束Delaunay三角化的实现

分析了约束Delaunay三角化中存在的边界一致性问题,给出了约束Delaunay三角化的理论依据,重点探讨了三维约束Delaunay三角化的可行性条件和范围,同时,给出了三维有限域约束Delaunay三角化的实现方法及其在石油地质勘探数据和机械零件方面的网格剖分实例.这种算法在复杂对象的科学计算和工程分析中发挥了重要作用.     

A Delaunay-based region-growing approach to surface reconstruction from unorganized points

This paper presents a Delaunay-based region-growing (DBRG) surface reconstruction algorithm that holds the advantages of both Delaunay-based and region-growing approaches. The proposed DBRG algorithm takes a set of unorganized sample points from the boundary surface of a three-dimensional object and produces an orientable manifold triangulated model with a correct geometry and topology that is faithful to the original object. Compared with the traditional Delaunay-based approach, the DBRG algorithm requires only one-pass Delaunay computation and needs no Voronoi information because it improves the non-trivial triangle extraction by using a region-growing technique. Compared with the traditional region-growing methods, the proposed DBRG algorithm makes the surface reconstruction more systematic and robust because it inherits the structural characteristics of the Delaunay triangulation, which nicely complements the absence of geometric information in a set of unorganized points. The proposed DBRG algorithm is capable of handling surfaces with complex topology, boundaries, and even non-uniform sample points. Experimental results show that it is highly efficient compared with other existing algorithms.     

一种基于三维Delaunay三角化的曲面重建算法

提出一种基于三维Delaunay三角化的区域增长式曲面重建方法。该方法以空间点云的Delaunay三角化为基础,结合局部区域增长的曲面构造,较以往方法具有人为参与更少、适用范围更广的优点。算法采用增量式插入点的方式构建空间Delaunay划分,采用广度优先算法,以外接圆最小为准则从Delaunay三角化得到的四面体中抽取出合适的三角片构成曲面。该算法的设计无须计算原始点集的法矢,且孔洞系数对重建的结果影响很小,重建出的三角网格面更符合原始曲面的几何特征。无论待建曲面是否是封闭曲面,本算法均可获得较好的重建效果。     

A hand-held approach to 3D reconstruction using light stripe projections onto a cube frame

The current paper presents a new light-striping approach for reconstructing a 3D model from a real object. The proposed system consists of a light plane projector, camera, and cube frame with LEDs attached. Instead of a strictly controlled camera and light emitters, a freely movable hand-held device is used that enables one to scan self-occluded objects. As in other light-striping systems, the correspondence problem is solved by projecting a light plane onto an object inside a frame. In the proposed system, the 3D coordinates of an illuminated light stripe are obtained using a calibration-free approach or dynamic optical triangulation. Furthermore, the computed 3D point data does not require any registration process because the data is directly measured based on unified world coordinates. Experimental results proved the accuracy of the measurements and consistency of the outcomes without any knowledge of the camera and light source parameters. An erratum to this article can be found at     

Estimation of search-space in 3D coronary artery reconstruction using angiographic biplane images

The three-dimensional reconstruction of heart arteries, using two radiographic images, is an ambiguous problem and results in multiple solutions. The correct solution can only be identified using a priori information. This work proposes a method to determine the number of possible solutions, which may be useful for the development of algorithms to solve this ambiguity problem. Our method proceeds by generating and counting all the possible solutions. Using real data, it was found that the number of solutions is moderate and an extensive search could be a feasible option at certain levels of the search process. The currently available computation power should be able to handle this solution space.     

利用立体图对的三维人脸模型重建算法

利用人脸正面立体图对重建三维人脸模型。无需三维激光扫描仪和通用人脸模型．获取立体图对并校正后,利用种子像素扩张算法实现图像匹配．种子像素选取算法能使足够数量的种子像素具有可靠视差;还提出了基于视差置信度的扩张算法,降低了视差图中大面积误匹配区域出现的可能性;最后,利用碟状粒子描述和Delaunay三角剖分重建三维人脸模型．实验结果表明,文中算法能够产生光滑逼真的三维人脸模型．     

Manifold surface reconstruction of an environment from sparse Structure-from-Motion data

The majority of methods for the automatic surface reconstruction of an environment from an image sequence have two steps: Structure-from-Motion and dense stereo. From the computational standpoint, it would be interesting to avoid dense stereo and to generate a surface directly from the sparse cloud of 3D points and their visibility information provided by Structure-from-Motion. The previous attempts to solve this problem are currently very limited: the surface is non-manifold or has zero genus, the experiments are done on small scenes or objects using a few dozens of images. Our solution does not have these limitations. Furthermore, we experiment with hand-held or helmet-held catadioptric cameras moving in a city and generate 3D models such that the camera trajectory can be longer than one kilometer.     

Provably correct reconstruction of surfaces from sparse noisy samples

Automated three-dimensional surface reconstruction is a very large and still fast growing area of applied computer vision and there exists a huge number of heuristic algorithms. Nevertheless, the number of algorithms which give formal guarantees about the correctness of the reconstructed surface is quite limited. Moreover such theoretical approaches are proven to be correct only for objects with smooth surfaces and extremely dense samplings with no or very few noise. We define an alternative surface reconstruction method and prove that it preserves the topological structure of multi-region objects under much weaker constraints and thus under much more realistic conditions. We derive the necessary error bounds for some digitization methods often used in discrete geometry, i.e. supercover and m-cell intersection sampling. We also give a detailed analysis of the behavior of our algorithm and compare it with other approaches.     

心内膜表面几何模型三维重建算法研究

心内膜三维表面重建是心内膜三维标测系统中的关键问题。为了满足实际应用需求, 根据采集到的散乱点云数据的特点, 提出了一种改进的泊松表面重建算法。在估计表面点云法向量的基础上, 对表面点云法向量进行法向量一致化处理, 有效地控制时间复杂度, 快速重建出平滑的心脏模型。针对泊松表面重建算法中构建MC曲面出现的二义性问题, 提出一种消除二义性的简化改进方法, 可以更加精确地获取模型逼真表面, 提高重建的速度和精度。同时, 可以根据医生的要求, 对重建出的模型实时修正, 满足临床应用。最后, 通过实验验证了算法的有效性和可行性。     

Localized Cocone surface reconstruction

We introduce a surface reconstruction algorithm suitable for large point sets. The algorithm is an octree-based version of the Cocone reconstruction algorithm [4], allowing independent processing of small subsets of the total input point set. When the points are sufficiently sampled from a smooth surface, the global guarantee of topological correctness of the original algorithm is preserved, together with the geometric accuracy guarantees.