Surface reconstruction of scanned human body using radial basis functions and adaptive partition of unity

It is important to reconstruct a continuous surface representation of the point cloud scanned from a human body. In this paper a new implicit surface method is proposed to reconstruct the human body surface from the points based on the combination of radial basis functions (RBFs) and adaptive partition of unity (PoU). The whole 3D domain of the scanned human body is firstly subdivided into a set of overlapping subdomains based on the improved octrees. The smooth local surfaces are then computed in the subdomains based on RBFs. And finally the global human body surface is reconstructed by blending the local surfaces with the adaptive PoU functions. This method is robust for the surface reconstruction of the scanned human body even with large or non-uniform point cloud which has a sharp density variation. Foundation item: the National Natural Science Foundation of China (No. 50575139) and the Shanghai Special Fund of Informatization (No. 088)     

基于机载LiDAR和Mean Shift算法提取森林密度

为获取森林密度信息,利用Mean Shift算法对森林点云进行单木分割提取森林密度信息.首先,以点云三维坐标和法向量作为特征向量,利用统计分析方法选择合适带宽及阈值,采用Mean Shift算法对点云进行初始分割;其次,对分割后的点云进行分析,加入灌木、杂草等过滤条件,得到树冠点云;然后,对树冠点云再次进行Mean Shift分割,并对每类树冠点云进行统计,以稳态点为粗略位置标记计算森林密度;最后,与地面实测数据进行验证.地面数据验证结果表明,平均计算精度达到90.0%以上,可满足林业应用需求;通过与分水岭法进行对比发现, Mean Shift方法获得的精度为92.5%,比分水岭方法70.0%高出22.5%,且避免了分水岭方法导致的过分割现象.      

基于K近邻和法向精度的点云精简算法

针对传统点云简化算法在精简散乱点云数据时经常丢失过多特征点的不足,提出了基于K近邻和法向精度的点云精简算法.该算法首先对输入的散乱点云数据建立K近邻索引,并剔除集群点及离群点,从而完成点云数据的预处理,然后对预处理后的数据进行Delaunay三角化,并重构三角网格面,最后依据法向精度进行非特征点剔除.仿真实验表明,该算法既能较大程度地精简点云数据,又能较好地保持原有模型的基本特征.     

Model-based gait representation via spatial point reconstruction

This paper proposed a novel model-based feature representation method to characterize human walking properties for individual recognition by gait. First, a new spatial point reconstruction approach is proposed to recover the coordinates of 3D points from 2D images by the related coordinate conversion factor (CCF). The images are captured by a monocular camera. Second, the human body is represented by a connected three-stick model. Then the parameters of the body model are recovered by the method of projective geometry using the related CCF. Finally, the gait feature composed of those parameters is defined, and it is proved by experiments that those features can partially avoid the influence of viewing angles between the optical axis of the camera and walking direction of the subject. Foundation item: the National Natural Science Foundation of China (No. 60675024)     

融合序列形态学算子的城区LiDAR滤波方法

为解决单一形态学算子在LiDAR数据滤波中的准确性和自动识别问题,提出了一种融合序列形态学算子的城区LiDAR滤波方法.在顾及多种形态学算子优势互补特性和LiDAR不同地物数据特点的基础上,首先利用形态学开运算及白top-hat变换剔除低粗差噪声和树木、汽车、电力线等小型地物,然后利用形态学梯度查找大型建筑物边缘,最后利用连通性分析和二值形态学重建方法剔除大型建筑物,获得准确的地面与地物分类点.使用ISPRS提供的不同复杂度9组城区测试数据进行实验,结果表明,本文方法的Ⅰ类、Ⅱ类及总误差均值分别达到6.90%、3.33%和5.44%,整体分类与自动识别性能优于常规滤波算法.      

Surface reconstruction by structured light projection

A rapid and practical method is proposed to reconstruct surface based on the linked structured light stripes which are produced by structured light projection. The subpixel points on a stripe are linked firstly one by one to form a stripe ensemble which is then transformed to a point ensemble in 3D space. The initial mesh with local optimization is generated by triangulating each two adjacent point ensembles. In order to obtain a better mesh, our improved edge flipping algorithm is employed to optimize the initial mesh globally. Because of employing the information of the linked structured stripes, our reconstruction algorithm is performed fastly. Moreover, the subpixel points on each stripe are already linked on the captured images such that they do not require the high sampling density. The experiments show that the proposed method constructs a surface rapidly and effectively.     

Curvature estimation of point set data based on the moving-least square surface

Curvature estimation is a basic step in many point relative applications such as feature recognition, segmentation, shape analysis and simplification. This paper proposes a moving-least square (MLS) surface based method to evaluate curvatures for unorganized point cloud data. First a variation of the projection based MLS surface is adopted as the underlying representation of the input points. A set of equations for geometric analysis are derived from the implicit definition of the MLS surface. These equations are then used to compute curvatures of the surface. Moreover, an empirical formula for determining the appropriate Gaussian factor is presented to improve the accuracy of curvature estimation. The proposed method is tested on several sets of synthetic and real data. The results demonstrate that the MLS surface based method can faithfully and efficiently estimate curvatures and reflect subtle curvature variations. The comparisons with other curvature computation algorithms also show that the presented method performs well when handling noisy data and dense points with complex shapes.     

多视点标定图像的交替迭代度量重建方法

提出了一种针对相机内部参数已标定的多视点图像交替迭代度量重建方法.该方法以目标空间中重建的3D点到匹配特征点的反投影线间的距离作为重建误差的测度,使误差函数形式上更简洁且具有明确的几何意义.重建过程通过对相机外部参数中的旋转矩阵、平移量和3D重建点交替迭代完成,其中平移量和3D点一起估计,避免了它们与旋转矩阵中的元素间的尺度差异引起的数值偏差.利用合成数据和真实图像的计算分析均表明本文方法有较高的重建精度,具有实用性.     

阶梯地形对西昌昔格达组三维地基地震动影响

为研究西昌昔格达组阶梯地形标高突变对地震动响应规律,选取攀钢西昌钒钛钢铁新基地地基工程为背景工程.以2个地基方案为研究对象,用有限元软件构建2个三维地基模型并模拟地震动作用下模型表面3个方向地震动加速度分布.通过分析得出如下结论:阶梯地形标高突变对水平方向加速度放大系数影响甚小,而竖直方向加速度放大系数骤增,但是否随着标高突变量增大而增大,有待进一步研究;从阶梯地形角点处向内侧延伸,竖直方向加速度放大系数又减小;竖直方向加速度放大系数随着输入地震动强度增大而减小;输入地震波强度越大,标高突变引起竖直方向加速度峰值增大越显著.     

基于激光雷达的无人驾驶障碍物检测和跟踪

针对激光雷达动态障碍物检测与跟踪过程中聚类适应性差、实时性低和跟踪准确度不高等问题，提出一种自适应的密度聚类算法和多特征数据关联方法，分别用于检测和跟踪. 首先，对激光雷达采集的点云进行路沿检测、感兴趣区域提取和地面分割等预处理，去除无关点云；然后，基于自适应的密度聚类算法对非地面的点云进行聚类，完成障碍物点云检测；最后，利用加权多特征数据关联算法结合卡尔曼滤波器实现对动态障碍物跟踪. 通过实验表明:本算法能够根据10 Hz的激光雷达数据实现对障碍物准确、稳定的检测和跟踪，且聚类时间缩短32%.      

带内外边界约束的平面点集Delaunay三角剖分

算法首先将离散点与约束边界点一起进行Delaunay三角剖分,形成初始Delaunay三角网,然后将约束边界上的各条约束线段通过局部更新依次嵌入已有的三角网,最后再删除多余的三角形,从而得到带内外边界约束的平面点集Delaunay三角剖分.     

平面交叉口竖向设计高程计算的综合法

采用方格网法将交叉口划分为四边形或三角形网格,将所有网格点作为设计计算点,利用圆心法确定各计算点的初始高程计算线,通过等分法、迭代法对初始高程计算线进行调整,并得到计算点的设计高程,根据网格点平面坐标及高程数据绘制设计等高线及三维表面效果图用于设计调整与质量检验。综合法所得竖向设计表面平顺,计算结果便于直接应用于工程的图纸设计与施工,该方法集成了方格网法、圆心法、等分法及等高线法的优点并加以改进,方法更加完善,工程适用性得到提高。     

一种新的基于LPMD的散射路径识别算法

NLOS（non-line-of-sight）非视距误差是地面无线定位的主要误差来源.为了从NLOS散射信号中识别出单次散射路径和多次散射路径,提出了一种新的基于LPMD（line-of-possible-mobile-device）目标可能位置线的识别算法.该算法以所有LPMD线的交点来计算初步参考点位置,并通过距离初步参考点较远的一部分交点对剩余较近的交点做负期望补偿,以修正参考点的位置,同时使用参考点到各LPMD线的直线距离来构造散射路径类型判决表达式,进行单/多次散射路径判决.在不同的仿真参数条件下,分别对普通场景和特殊场景进行了散射路径识别仿真实验,结果表明,当侦测站和目标点之间的距离达到4 km时,本文算法的虚警和漏警概率分别只有3%和9%,比原有基于LPMD算法的分别降低了21%和8%.      

基于三维模型重构技术的公路预制构件尺寸检验评价方法

为使公路工程异形混凝土预制构件的制造尺寸检验评价适应工业化建造要求,应用三维模型重构技术检验评价了异形混凝土预制构件尺寸,提出了高精度、自动化异形混凝土预制构件尺寸检验评价方法,包括三维模型重构、点云数据处理和检验评价体系3个环节;总结了基于三维摄影的点云模型重构技术的原理和关键环节,研究了基于坐标转换和包围盒的无关点...     

点云数据配准算法的研究

点云配准是点云数据处理的关键,直接影响最后合成结果和模型精度。目前,点云配准方法普遍存在对配准数据初始位姿要求高的缺点。将点云配准分为两个阶段：第一阶段是基于同名点配准,即粗配准,采用人机交互式,配准过程耗时短,节约时间;第二阶段是精配准,在粗配准后,依据最小二乘原理,用间接平差思想,通过最近点迭代算法对点云数据快速配准,并采用目标点集中、目标点坐标与转入目标点集中的点坐标中误差为指标,评价配准精度。进行粗配准的精配准不仅速度快、耗时短,并且可以避免因局部收敛而带来的局部最小问题。试验表明该方法有效可行。     

Improved Kernel Possibilistic Fuzzy Clustering Algorithm Based on Invasive Weed Optimization

Fuzzy c-means(FCM) clustering algorithm is sensitive to noise points and outlier data, and the possibilistic fuzzy c-means(PFCM) clustering algorithm overcomes the problem well, but PFCM clustering algorithm has some problems: it is still sensitive to initial clustering centers and the clustering results are not good when the tested datasets with noise are very unequal. An improved kernel possibilistic fuzzy c-means algorithm based on invasive weed optimization(IWO-KPFCM) is proposed in this paper. This algorithm first uses invasive weed optimization(IWO) algorithm to seek the optimal solution as the initial clustering centers, and introduces kernel method to make the input data from the sample space map into the high-dimensional feature space. Then, the sample variance is introduced in the objection function to measure the compact degree of data. Finally, the improved algorithm is used to cluster data. The simulation results of the University of California-Irvine(UCI) data sets and artificial data sets show that the proposed algorithm has stronger ability to resist noise, higher cluster accuracy and faster convergence speed than the PFCM algorithm.     

基于特征数据分块自适应切片的空洞修补

针对常用的空洞修补方法在修复具有多种曲面类型的空洞时失效和所修复的曲面不光顺等缺点,提出基于特征数据分块自适应切片的空洞修补。首先,在考虑特征信息的情况下基于聚类对散乱点云进行分块;然后利用特征进行自适应切片,获得曲线并进行拟合;最后,在线上取点填充缺失的点云,最终对完整的点云模型进行曲面重构建立实体模型。试验结果表明,采用自适应切片法修补空洞能够保留特征,所填充的点云数据精度较高,能够满足后续建模的需要。此外对该方法填充的点云进行了曲面重构及光顺,结果令人满意。     

城市轨道交通社会效益的模糊综合评价

城市轨道交通属于公共产品,从已经投入运营的轨道交通来看,由于其初期投资成本大、投资回收期长,不论国际还是国内能够真正盈利的线路不多。但是轨道交通将极大地促进所在城市和地区的经济发展,所产生的宏观社会效益远远超过其建设者或运营者本身的微观经济效益。介绍了轨道交通社会效益的模糊综合评价方法,并以成都地铁为实例对其社会效益进行了模糊综合评价,以期为进一步的城市轨道交通项目投资决策提供参考。     

基于车载连续序列图像的道路曲率计算方法

提出一种基于车载连续序列图像的道路曲率计算方法.算法首先利用车载视 觉系统进行内外参数标定实现对路面车道线的三维重建,利用三维重建误差模型对重建 的数据点进行误差估计,并对数据点进行选弃.对序列图像中路面车道线重建出来的曲线 采用ICP 算法进行曲线匹配,并将匹配后的曲线映射到统一的参考坐标系中.最后利用匹 配曲线上的数据点进行圆周拟合,计算道路曲率.实验中利用真实的车载连续序列图像对 算法进行验证.针对曲率半径分别为96 m和430 m两段不同程度的弯道,利用本文算法计 算对应道路的曲率半径.结果表明,本文算法能够精确地计算出不同弯道的道路曲率,特 别是针对平缓弯道的曲率计算,比基于单幅图像的曲率计算方法更加准确与稳定.