基于邻域曲率的低特征辨识度点云配准方法

在对特征辨识度低的点云进行配准的过程中,传统的基于局部特征提取和匹配的方法通常精度不高,而基于全局特征匹配的方法精度和效率也难以保证。针对这一问题,提出一种改进的局部特征配准方法。在初步配准阶段,设计了一种基于法向量投影协方差分析的关键点提取方法,结合快速特征直方图(FPFH)对关键点进行特征描述,定义多重匹配条件对特征点进行筛选,最后将对应点的最近距离之和作为优化目标进行粗匹配;在精配准阶段,采用以点到平面的最小距离作为迭代优化对象的改进迭代最近点(ICP)算法进行精确配准。实验结果表明,在配准特征辨识度低的点云时,相较于其他三种配准方法,该方法能保持高配准精度的同时降低配准时间。     

散乱点云数据配准算法

提出一种以物体表面上不附加任何几何和拓扑信息的散乱点集为处理对象，自动进行点云数据配准的算法．该算法针对待配准的2组点云数据，根据测点及其邻域点估算每个点的曲面法矢，并对法矢方向进行调整，使其指向曲面的同一侧；然后计算各个测点的曲率．根据每个测点的曲率来识别出2组点云数据中可以匹配的点对集合。计算将每一个点对的法矢方向映射为一致的三维空间变换，采用几何哈希方法找出使得最多数量的点对法矢一致的变换，运用该变换将散乱点云作初次配准．以初次配准后的结果作为新的初始位置，将匹配点对集合中的所有点对采用最近点迭代法进行二次配准，从而实现了2组散乱数据的精确配准．应用实例表明，该算法效果良好．     

一种基于改进投影方法的点云拼接算法*

针对传统ICP（iterative closest point）算法在收敛速度或拼接精度上无法同时满足实时测量要求的问题,提出了一种适用于单、双目结构光三维测量系统的快速且高精度的点云拼接算法。该算法首先将参考视点云上的采样点反向投影到目标视点云的2D成像平面上,然后再将2D反向投影点正向投影到目标视点云上,展示了一种由目标视投影点到采样点法线上的投影直至收敛于线—面交点的迭代过程。实际测量结果表明,该算法在保证拼接精度的同时显著提高了收敛速度,是一种具有很高实用价值的拼接算法。     

Hand-held 3D scanning based on coarse and fine registration of multiple range images

A hand-held 3D scanning technique is proposed to reconstruct 3D models of real objects. A sequence of range images captured from a hand-held stereo camera is automatically registered to a reference coordinate system. The automated scanning process consists of two states, coarse and fine registration. At the beginning, scanning process starts at the fine registration state. A fast and accurate registration refinement technique is used to align range images in a pair-wise manner. If the refinement technique fails, the process changes to the coarse registration state. A feature-based coarse registration technique is proposed to find correspondences between the last successful frame and the current frame. If the coarse registration successes, the process returns to the fine registration state again. A fast point-to-plane refinement technique is employed to do shape-based registration. After the shape-based alignment, a texture-based refinement technique matches texture features to enhance visual appearance of the reconstructed models. Through a graphic and video display, a human operator adjusts the pose of the camera to change the view of the next acquisition. Experimental results show that 3D models of real objects are reconstructed from sequences of range images.     

Localization of an unmanned ground vehicle based on hybrid 3D registration of 360 degree range data and DSM

A computer vision technique to identify the location of an outdoor unmanned ground vehicle (UGV) is presented. The proposed technique is based on hybrid 3D registration of 360 degree laser range data to a digital surface model (DSM). Range frames obtained from 48 laser detectors are aligned with the reference coordinate system of the DSM. Three novel approaches are proposed for accurate and fast 3D registration of range data and the DSM. First, a two-step hybrid 3D registration technique is proposed. A pair-wise registration step of two consecutive range frames is followed by a refinement step using a layered DSM. Second, a fast projection-based pair-wise registration is proposed by employing rasterized 360 degree range frames. Third, a high elevation DSM is divided into several elevation layers and correspondence search is done near the vehicle’s current elevation. This reduces the number of matching outliers and facilitates fast localization. Experimental results show that the proposed approaches yield better performance in 3D localization compared to conventional 3D registration techniques. Error analysis on five outdoor paths is presented with respect to ground truth.     

利用角度签名进行3维表面配准

3维表面的配准在3维物体重建、场景检测和物体识别过程中起着重要的作用。为此提出了一种新的3维表面表示方法——角度签名(angle signature),并将其用于3维表面配准。该表示方法将表面的局部几何信息表示成为1维的向量,具有对刚体变换的不变性。由于其简洁的表示方式,可以实现表面的快速配准。此外,该方法较其他3维表面的表示方法具有更强的鲁棒性。在实际应用中,为了提高表面配准的速度,首先筛选出特征点,然后利用特征点寻找表面之间的对应关系,从而将刚体变换的参数求出,实现表面的配准。实验结果表明,采用角度签名实现物体表面配准具有较快的速度和较高的精度。     

Simultaneous Registration of Multiple Corresponding Point Sets

We present a new technique for the simultaneous registration of multiple corresponding point sets with rigid 3D transformations. This class of problems is a generalization of the classic pairwise point set registration task, involving multiple views with multiple correspondences existing between them. The proposed technique requires the computation of a constant matrix which encodes the point correspondence information, followed by an efficient iterative algorithm to compute the optimal rotations. The optimal translations are then recovered directly through the solution of a linear equation system. The algorithm supports weighting of data according to confidence, and we show how it may be incorporated into two robust estimation frameworks to detect and reject outlier data. We have integrated our method into a generalized multiview ICP surface matching system and tested it with synthetic and real data. These tests indicate that the technique is accurate and efficient. The algorithm also compares favorably to another multiview technique from the literature.     

改进的工业CT图像与CAD模型的比对检测

改进了一种基于工业计算机断层成像(industrial computed tomography,ICT)图像与计算机辅助设计(computer aided design,CAD)模型的比对检测算法,分析工件制造误差。首先对工业CT图像用三维Otsu法进行阈值分割,并分别提取边缘面与角点特征;然后对工业CT图像角点特征与工件的CAD模型用文中研究的旋转投影法求取方向包围盒,进而实现粗配准;再结合角点特征点集和奇异值分解—迭代最近点算法进行精配准,最近点对的求取用k-d树进行加速;最后在边缘面上显示误差。实验结果表明,该方法在工件比对检测过程中,粗配准精度更高,适应性更好。整个比对检测过程更加高效,速度上有了较大的提高。     

基于SIFT算法及阈值筛选的点云配准技术研究

随着三维测量技术应用领域的逐渐拓宽,点云数据处理技术的需求日益迫切,而多视点点云配准,是其中的基础技术环节;在此针对传统ICP算法鲁棒性差、对迭代初值敏感、计算效率低等缺点,提出一种SIFT算法与阈值筛选相结合的点云配准算法;在参考点云和待配准点云中,通过计算SIFT关键点及各点主曲率,获得初始匹配点集;然后根据相似三角形阈值和法向量夹角阈值,进一步优化点对间的旋转平移关系;实验结果证明,相对于传统算法,改进算法能够以更短的时间来获得准确的配准效果,并且其自动化程度高以及能有效提高点云配准的效率和精度。