Improved Iterative Closest Point(ICP) 3D point cloud registration algorithm based on point cloud filtering and adaptive fireworks for coarse registration

ABSTRACT

Aiming at the problem of long computation time and poor registration accuracy in the current three-dimensional point cloud registration problem, this paper presents a k-dimensional Tree(KD-tree) improved ICP algorithm(KD-tree_ICP) that combines point cloud filtering and adaptive fireworks algorithms for coarse registration. On the basis of the typical KD-tree improved ICP algorithm, the point cloud filtering process and adaptive firework coarse registration process are added. Firstly, the point cloud data acquired by the 3D laser scanner is filtered. And then the adaptive fireworks algorithm is used to perform coarse registration on the filtered point cloud data. Next, the KD-tree_ICP algorithm is used to perform accurate registration on the basis of coarse registration, and the obtained translation and rotation relations are applied to the original point cloud data to obtain the result after registration. Finally, 3D point clouds of physical models of five statues are used for experimental verification, including error analysis, stability analysis and comparison with other algorithms. The experimental results show that the method proposed in this paper has greatly improved the calculation speed and accuracy, and the algorithm is stable and reliable, which can also be applied to the reconstruction of 3D building models, restoration of cultural relics, precision machining and other fields.     

Towards automatic generation of as-built BIM: 3D building facade modeling and material recognition from images

As-built building information model(BIM) is an urgent need of the architecture, engineering, construction and facilities management(AEC/FM) community. However, its creation procedure is still labor-intensive and far from maturity. Taking advantage of prevalence of digital cameras and the development of advanced computer vision technology, the paper proposes to reconstruct a building facade and recognize its surface materials from images taken from various points of view. These can serve as initial steps towards automatic generation of as-built BIM. Specifically, 3D point clouds are generated from multiple images using structure from motion method and then segmented into planar components, which are further recognized as different structural components through knowledge based reasoning. Windows are detected through a multilayered complementary strategy by combining detection results from every semantic layer. A novel machine learning based 3D material recognition strategy is presented. Binary classifiers are trained through support vector machines. Material type at a given 3D location is predicted by all its corresponding 2D feature points.Experimental results from three existing buildings validate the proposed system.     

空地融合的城市道路基础设施数字化技术研究

城市道路基础设施三维模型的重构,在城市道路BIM应用与数字化领域具有重大意义;针对城市交通基础设施数字化重构的需求,对车载激光扫描与无人机倾斜摄影采集技术进行综合运用,提出一套从信息采集、空地点云配准、点云分割到三维重构的完整技术方法;首先使用车载激光扫描技术和无人机倾斜摄影技术对交通基础设施信息进行采集,并使用运动恢复结构算法(SfM,structure from motion)生成基础设施空地点云;其次使用迭代最近点法(ICP,iterative closest point)对空地点云进行精配准,然后利用基于PointNet网络的方法对融合点云进行语义分割;最后对分割出的交通基础设施对象进行三维重构;提出的空地融合的城市交通基础设施数字化技术能够高效地实现交通基础设施重构,为城市交通基础设施数字化提供基础、为后续交通专业领域的应用研究提供便利.     

Film and television industry cloud exhibition design based on 3D imaging and virtual reality

The three-dimensional virtual scene can provide users with a visual three-dimensional virtual environment, with various multimedia channels such as sound, video, force feedback equipment, etc., to bring users a completely immersive interactive experience. This paper introduces 3D imaging and virtual reality technology in the film and television industry cloud exhibition, and develops a virtual display platform. First of all, this paper divides the registration into two processes: camera calibration and joint calibration of the camera and laser scanner based on the calibration results. Camera calibration can determine the plane model of the calibration board in the camera coordinate system, and the joint calibration uses the RANSAC algorithm to extract the point cloud of the plane model of the calibration board, and then optimizes the distance between the points in the plane model point cloud and the corresponding plane in the camera coordinate system Find the optimal transformation between the two sets of data, and then calculate the registration relationship between the point cloud and the image. Secondly, this article conducts a demand analysis of the film and television industry cloud exhibition platform based on virtual reality technology, including the business goals set by the platform, platform system analysis, overall design, and system operating environment and configuration requirements. This model provides a feasible solution for the visual interaction of the cloud exhibition design of the film and television industry.     

动态环境中多帧点云融合算法及三维目标检测算法研究

低线束激光雷达扫描的点云数据较为稀疏,导致无人驾驶环境感知系统中三维目标检测效果欠佳,通过多帧点云配准可实现稀疏点云稠密化,但动态环境中的行人与移动车辆会降低激光雷达的定位精度,也会造成融合帧中运动目标上的点云偏移较大。针对上述问题,提出了一种动态环境中多帧点云融合算法,利用该算法在园区道路实况下进行三维目标检测,提高了低线束激光雷达的三维目标检测精度。利用16线和40线激光雷达采集的行驶路况数据进行实验,结果表明该算法能够增强稀疏点云密度,改善低成本激光雷达的环境感知能力。     

Applications of 3D point cloud data in the construction industry: A fifteen-year review from 2004 to 2018

3D point cloud data obtained from laser scans, images, and videos are able to provide accurate and fast records of the 3D geometries of construction-related objects. Thus, the construction industry has been using point cloud data for a variety of purposes including 3D model reconstruction, geometry quality inspection, construction progress tracking, etc. Although a number of studies have been reported on applying point cloud data for the construction industry in the recent decades, there has not been any systematic review that summaries these applications and points out the research gaps and future research directions. This paper, therefore, aims to provide a thorough review on the applications of 3D point cloud data in the construction industry and to provide recommendations on future research directions in this area. A total of 197 research papers were collected in this study through a two-fold literature search, which were published within a fifteen-year period from 2004 to 2018. Based on the collected papers, applications of 3D point cloud data in the construction industry are reviewed according to three categories including (1) 3D model reconstruction, (2) geometry quality inspection, and (3) other applications. Following the literature review, this paper discusses on the acquisition and processing of point cloud data, particularly focusing on how to properly perform data acquisition and processing to fulfill the needs of the intended construction applications. Specifically, the determination of required point cloud data quality and the determination of data acquisition parameters are discussed with regard to data acquisition, and the extraction and utilization of semantic information and the platforms for data visualization and processing are discussed with regard to data processing. Based on the review of applications and the following discussions, research gaps and future research directions are recommended including (1) application-oriented data acquisition, (2) semantic enrichment for as-is BIM, (3) geometry quality inspection in fabrication phase, and (4) real-time visualization and processing.     

基于特征点动态选择的三维人脸点云模型重建

针对典型的点云配准方法中伪特征点过多导致配准效率低和配准结果不精确的问题,提出一种基于特征点动态选择的三维人脸点云模型重建方法。该方法在粗配准阶段,采用动态特征矩阵求解法获取粗匹配特征变换矩阵以避免伪特征点的干扰。在精配准过程中,采用二次加权法向量垂直距离法在人脸流形表面选择更有效的特征点以减少伪特征点的数量,并采用基于特征融合与局部特征一致性的迭代最近点方法进行精配准。经过对比实验验证了算法的可行性,实验结果表明,提出算法能够实现高精度且快速的三维人脸点云模型重建,且均方根误差达到1.816 5 mm,相较于其他算法,在模型重建精度和效率方面都有所提升,具有良好的应用前景。     

面向三维重建的自适应列文伯格-马夸尔特点云配准方法

针对三维重建时点云配准过程易受环境噪声、点云曝光、光照、物体遮挡等因素的影响,以及传统ICP配准算法配准精度低、耗时长等问题,提出一种基于自适应列文伯格-马夸尔特迭代式的点云配准方法。首先,对初始点云数据采用统计滤波和体素栅格滤波相结合的方式进行降噪预处理;然后,对滤波后的点云进行分层,剔除位于层外的外点数据,以提高后续点云配准的精度;针对传统点云特征描述方法计算量大的问题,使用平滑度参数提取点云特征,以提升点云配准的效率;最后,根据点云特征建立帧间点到线及点到面的约束关系,采用改进的列文伯格-马夸尔特(Levenberg-Marquardt)方法完成点云配准,构建较理想的三维重建模型。实验结果表明,提出的点云配准方法适用于室内及室外场景的三维重建,环境适应性强,且点云配准精度和效率都有较大提升。     

三维点云配准方法研究进展

点云是一种3维表示方式,在广泛应用的同时产生了对点云处理的诸多挑战。其中,点云配准是一项非常值得研究的工作。点云配准旨在将多个点云正确配准到同一个坐标系下,形成更完整的点云。点云配准要应对点云非结构化、不均匀和噪声等干扰,要以更短的时间消耗达到更高的精度,时间消耗和精度往往是矛盾的,但在一定程度上优化是有可能的。点云配准广泛应用于3维重建、参数评估、定位和姿态估计等领域,在自动驾驶、机器人和增强现实等新兴应用上也有点云配准技术的参与。为此,研究者开发了多样巧妙的点云配准方法。本文梳理了一些比较有代表性的点云配准方法并进行分类总结,对比相关工作,尽量覆盖点云配准的各种形式,并对一些方法的细节加以分析介绍。将现有方法归纳为非学习方法和基于学习的方法进行分析。非学习方法分为经典方法和基于特征的方法;基于学习的方法分为结合了非学习方法的部分学习方法和直接的端到端学习方法。本文分别介绍了各类方法的典型算法,并对比总结算法特性,展望了点云配准技术的未来研究方向。     

Automated continuous construction progress monitoring using multiple workplace real time 3D scans

In recent years, exponential growth has been detected in research efforts focused on automated construction progress monitoring. Despite various data acquisition methods and approaches, the success is limited. This paper proposes a new method, where changes are constantly perceived and as-built model continuously updated during the construction process, instead of periodical scanning of the whole building under construction. It turned out that low precision 3D scanning devices, which are closely observing active workplaces, are sufficient for correct identification of the built elements. Such scanning devices are small enough to fit onto workers’ protective helmets and on the applied machinery. In this way, workers capture all workplaces inside and outside of the building in real time and record partial point clouds, their locations, and time stamps. The partial point clouds are then registered and merged into a complete 4D as-built point cloud of a building under construction. Identification of as-designed BIM elements within the 4D as-built point cloud then results in the 4D as-built BIM. Finally, the comparison of the 4D as-built BIM and the 4D as-designed BIM enables identification of the differences between both models and thus the deviations from the time schedule. The differences are reported in virtual real-time, which enables more efficient project management.     

基于特征点和改进ICP的三维点云数据配准算法

在光学非接触三维测量中,复杂对象的重构需要多组测量数据的配准。最近点迭代(ICP)算法是三维激光扫描数据处理中点云数据配准的一种经典的数学方法,为了获得更好的配准结果,在ICP算法的基础之上,提出了结合基于特征点的等曲率预配准方法和邻近搜索ICP改进算法的精细配准,自动进行点云数据配准的算法,经对牙齿点云模型实验发现,点云数据量越大,算法的配准速度优势越明显,采用ICP算法的运行时间(194.58 s)远大于本算法的运行时间(89.13 s)。应用实例表明:该算法具有速度快、精度高的特点,算法效果良好。     

A Theory of Minimal 3D Point to 3D Plane Registration and Its Generalization

Registration of 3D data is a key problem in many applications in computer vision, computer graphics and robotics. This paper provides a family of minimal solutions for the 3D-to-3D registration problem in which the 3D data are represented as points and planes. Such scenarios occur frequently when a 3D sensor provides 3D points and our goal is to register them to a 3D object represented by a set of planes. In order to compute the 6 degrees-of-freedom transformation between the sensor and the object, we need at least six points on three or more planes. We systematically investigate and develop pose estimation algorithms for several configurations, including all minimal configurations, that arise from the distribution of points on planes. We also identify the degenerate configurations in such registrations. The underlying algebraic equations used in many registration problems are the same and we show that many 2D-to-3D and 3D-to-3D pose estimation/registration algorithms involving points, lines, and planes can be mapped to the proposed framework. We validate our theory in simulations as well as in three real-world applications: registration of a robotic arm with an object using a contact sensor, registration of planar city models with 3D point clouds obtained using multi-view reconstruction, and registration between depth maps generated by a Kinect sensor.     

基于 BIM 及 3D GIS 的城市水务应用项目管理平台

通过分析上海市2018年水务重大工程建设项目的现状及水务重大工程2019年建设计划,上海市水务水利工程数量、体量和复杂度逐年增加。为了贯彻落实上海市及水务局关于推广BIM应用技术的文件精神,顺应政府工程监管信息化的发展,缓解工程管理监管难度,上海市水务局在前期已开展的相关BIM模型轻量化展示、3D GIS等关键技术预研的基础上,决定建设BIM数据中心及相应的水务应用管理协同平台。项目管理平台利用云架构,大数据,BIM,3D GIS,无人机数据采集等技术,系统基于B/S结构,BIM模型轻量化采用WebGL 3D绘图协议,实现二维与三维结合、实景和BIM模型结合。该平台在模型共享、工程数据共享、工程展示及监管中发挥了一定作用。     

基于 AISI 网络的 BIM 三维重建方法研究

自动从点云数据生成建筑信息模型(BIM)一直是建筑自动化领域的研究热点。基于 传统算法的建筑自动三维重建的缺点包括人工设计特征,识别过程复杂,应用场景有限等。随 着三维机器学习领域的不断成熟,处理点云便有了新的手段。通过引入实例分割中的 ASIS 网 络框架对点云进行处理,即从扫描点云场景中自动分割和分类建筑构建元素并得到实例分割矩 阵。接着,基于包围盒假设从得到的实例分割矩阵中提取建筑构件外轮廓参数,并将外轮廓参 数和分割的语义分类结果作为 BIM 建模的构件参数。最后,将这些提取的构件参数输入到自制 的 IFC 生成器中,自动生成基于工业基础类(IFC)标准的 BIM 模型。实验表明,利用无噪点点 云方法,可实现基于曼哈顿世界假设下的室内单房间的三维重建。     

A robot hand-eye calibration method of line laser sensor based on 3D reconstruction

In the robotic eye-in-hand measurement system, a hand-eye calibration method is essential. From the perspective of 3D reconstruction, this paper first analyzes the influence of the line laser sensor hand-eye calibration error on the 3D reconstructed point clouds error. Based on this, considering the influence of line laser sensor measurement errors and the need for high efficiency and convenience in robotic manufacturing systems, this paper proposes a 3D reconstruction-based robot line laser hand-eye calibration method. In this method, combined with the point cloud registration technique, the newly defined error-index more intuitively reflects the calibration result than traditional methods. To raise the performance of the calibration algorithm, a Particle Swarm Optimization - Gaussian Process (PSO-GP) method is adopted to improve the efficiency of the calibration. The experiments show that the Root Mean Square Error (RMSE) of the reconstructed point cloud can reach 0.1256 mm when using the proposed method, and the reprojection error is superior to those using traditional hand-eye calibration methods.     

基于牙颌模型的散乱点云配准技术研究

在牙齿三维矫正中需要对牙齿进行排列,常用方法是通过人机交互完成,效率不高。提出了一种基于粒子群的自动化排牙方法,将每颗牙齿上的特征点到标准牙弓曲线的距离和作为目标函数,利用粒子群算法对解空间进行搜索,在搜索过程中加入约束条件,得到牙齿移动的最终位置。利用算法对牙齿进行排列,可以省去人机交互中的平移等操作。实验结果表明：该算法能够有效地用于牙齿三维矫正中,提高了排牙效率。     

基于QT的机载三维激光扫描仪软件系统设计

随着测绘技术的发展,利用机载三维激光扫描仪获取点云数据,从点云数据中提取模型信息成为现代测绘技术的一种发展趋势. 点云数据处理的相关应用也越来越多,点云数据的处理软件参差不齐,需求和功能也各不相同. 针对上述问题,在基于QT编程平台下,利用PCL开发机载三维激光扫描仪点云数据处理软件,集中处理点云数据. 该系统由点云数据读写、三维显示、点云滤波、网格重构、点拾取、点云分割及NARF关键点提取等功能模块组成. 各模块采用面向对象的思想设计,功能易于扩展,以完成进一步的测绘工作. 实践表明,该系统具有良好的工程实用价值,可以快速完成机载三维激光扫描仪的数据处理工作.     

改进ICP算法实现多视点云精确配准研究

复杂面形的三维整体测量能否顺利完成取决于不同视下测得的三维点云的配准精度。研究表明:采用点到点,点到三角面配准方法易受噪声干扰,采用面形比较计算量大,且在平面和标准球面情况下容易失效。以粗配准标记点所在的立方体区域为重合区域,使用点到点的多邻接三角面距离最近的点对作为初始匹配点,并根据几何结构最大相似原则对所求得的多个粗匹配点对进行筛选,再对筛选后的点对应用最近点迭代(ICP)算法。改进后的ICP算法实现了重合区域的快速自动定位,实现了不同视下点云的快速精确配准,在多个实例下获得了配准精度优于0.01 mm的实验结果。