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Robust affine iterative closest point algorithm with bidirectional distance

IET COMPUTER VISION 2012年第3期6卷 252-261页

作者： Zhu, J. Du, S. Yuan, Z. Liu, Y. Ma, L. Xi An Jiao Tong Univ Sch Software Engn Xian 710049 Shannxi Peoples R China Xi An Jiao Tong Univ Inst Artificial Intelligence & Robot Xian 710049 Shannxi Peoples R China

This study proposes a robust affine iterative closest point (icp) algorithm based on bidirectional distance for the registration of m-dimensional (m-D) point sets. Since the affine registration problem can be formulated as a least square (LS) problem by incorporating an affine transformation, this study first analyses the ill-posed problem of the affine registration and turn it into well-posed one by introducing the bidirectional distance into the LS formulation. Then, the corresponding affine icp algorithm is proposed to solve the well-posed problem. By using the bidirectional distance, the proposed algorithm can directly estimate the affine transformation and converge monotonically to a local minimum from any given initial parameters. To obtain the desired global minimum, good initial parameters can be estimated by independent component analysis (ICA) technique. The proposed approach makes no geometric assumptions on point sets, so it is a general framework for affine registration of m-D point sets. Experimental results demonstrate its robustness and accuracy compared with the current state-of-the-art approaches.

关键词： affine transformation affine registration problem icp algorithm bidirectional distance Computer vision and image processing techniques image registration m-dimensional point sets independent component analysis Integral transforms affine transforms Optical, image and video signal processing least square problem well-posed problem ill-posed problem robust affine iterative closest point algorithm iterative methods

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RECONSTRUCTION OF PROPELLER AND COMPLEX SHIP HULL SURFACE BASED ON REVERSE ENGINEERING

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JOURNAL OF MARINE SCIENCE AND TECHNOLOGY-TAIWAN 2019年第6期27卷 498-504页

作者： Guan, Guan Gu, Wen-wen Dalian Univ Technol Sch Naval Architecture Dalian 116024 Peoples R China Dalian Univ Technol State Key Lab Struct Anal Ind Equipment Dalian 116024 Peoples R China

To quickly obtain the digital model of ship surface for detection and redesign, a reconstruction method for propeller and ship surface is proposed. Three-dimensional point cloud data of ship hull was obtained by laser scanning technology and the cloud data was preprocessed by iterative closest point (icp) algorithm and chord deviation method. Then the surface was reconstructed with traditional surface modeling method and fast surface modeling method. By comparing the reconstructed surface with the initial point cloud data, the error of the reconstructed model was obtained. The result shows that the reconstructed surface gains good smoothness and small error. With this method, ship surface can be reconstructed quickly and the reconstructed digital model is of good quality which can be used in detection and redesign.

关键词： reverse engineering ship surface propeller point cloud reconstruction icp algorithm

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Multi-view point cloud registration with adaptive convergence threshold and its application in 3D model retrieval

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MULTIMEDIA TOOLS AND APPLICATIONS 2020年第21-22期79卷 14793-14810页

作者： Li, Yaochen Liu, Ying Sun, Rui Guo, Rui Zhu, Li Qi, Yong Xi An Jiao Tong Univ Sch Software Engn Xian Shaanxi Peoples R China Xi An Jiao Tong Univ Dept Comp Sci & Technol Xian Shaanxi Peoples R China

Multi-view point cloud registration is a hot topic in the communities of artificial intelligence and multimedia technology. In this paper, we propose a novel framework to reconstruct 3D models with a multi-view point cloud registration algorithm with adaptive convergence threshold, and apply it to 3D model retrieval subsequently. The iterative closest point (icp) algorithm is implemented with an adaptive convergence threshold, and further combines with a motion average algorithm for the registration of multi-view point cloud data. After the registration process, the applications are designed for 3D model retrieval. The geometric saliency map is computed based on the vertex curvatures. The test facial triangles are selected to compare with the standard facial triangle. The face and non-face models are then discriminated. The experiments and comparisons demonstrate the effectiveness of the proposed framework.

关键词： Point cloud registration icp algorithm Convergence threshold Geometric saliency 3D model retrieval

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Coarse-fine point cloud registration based on local point-pair features and the iterative closest point algorithm

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APPLIED INTELLIGENCE 2022年第11期52卷 12569-12583页

作者： Yue, Xiaofeng Liu, Zeyuan Zhu, Juan Gao, Xueliang Yang, Baojin Tian, Yunsheng Changchun Univ Technol Mech & Elect Engn Changchun Jilin Peoples R China

3D point cloud registration has a wide range of applications in object shape detection, robot navigation and 3D reconstruction. Aiming at the problems of the traditional icp registration algorithm, such as slow convergence speed and high requirements for the initial point cloud position, this paper proposes a coarse-fine point cloud registration method based on a fast and robust local point-pair feature (LPPF) and the icp algorithm. The LPPF feature descriptor is an improved descriptor for the local application of classic point-pair features and is a histogram descriptor formed by counting the feature information of the local point cloud neighborhood. This paper completes point cloud registration through keypoint extraction, LPPF feature description, feature matching, coarse registration and fine registration. To verify the effectiveness of this method, under the evaluation indices of L-1, RMSE and MAE, we analyzed the experimental results from the three aspects of descriptors, coarse registration and coarse-fine registration. Under Gaussian noise conditions, LPPF compared to the second-ranked descriptor, the L-1 scores of LPPF on the Stanford, Kinect and Princeton datasets increased by 12%, 12.4% and 9.1%, respectively. The coarse registration experiment is compared with 5 classic descriptors on 3 commonly used datasets. The LPPF feature descriptor has higher registration accuracy and less registration time. Finally, the coarse-fine registration experiment shows that our method can reduce the number of iterations of the icp algorithm by 77% under optimal conditions.

关键词： Point cloud registration Local point-pair feature icp algorithm Feature matching Coarse-fine registration

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Study of parameterizations for the rigid body transformations of the scan registration problem

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COMPUTER VISION AND IMAGE UNDERSTANDING 2010年第8期114卷 963-980页

作者： Nuechter, Andreas Elseberg, Jan Schneider, Peter Paulus, Dietrich Jacobs Univ Bremen Sch Sci & Engn D-28759 Bremen Germany Univ Koblenz Landau Inst Computat Visualist Act Vis Grp D-56070 Koblenz Germany

The iterative closest point (icp) algorithm is the de facto standard for geometric alignment of three-dimensional models when an initial relative pose estimate is available. The basis of the algorithm is the minimization of an error function that takes point correspondences into account. Four closed-form solution methods are known for minimizing this function. This paper presents novel linear solutions to the scan registration problem, i.e., to the problem of putting and aligning 3D scans in a common coordinate system. We extend the methods for registering n-scans in a global and simultaneous fashion, such that the registration of the nth scan influences all previous registrations in one step. (C) 2010 Elsevier Inc. All rights reserved.

关键词： 3D scan matching 3D point cloud registration icp algorithm

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A measurement method of the belt grinding allowance of hollow blades based on blue light scanning

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INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY 2021年第9-10期116卷 3295-3303页

作者： Xiao, Guijian Liu, Shuai Zhang, Youdong Wu, Yuan Chen, Bengqiang Song, Shayu Chongqing Univ Coll Mech Engn Chongqing 400044 Peoples R China

The high performance of aero-engines requires light-weight aero-engine blades, so hollow structures have been widely used in aero-engine blades. At present, the measurement of aero-engine blades is mainly carried out with coordinate measuring machines (CMM). This method can measure most of the aero-engine blades through direct contact. However, the complex surface, the chord width, and the large torsion of the profile of a hollow blade lead to measurement difficulties. In addition, the surface contact machining characteristics of belt grinding largely depend on the known data of the detected surface, so the CMM cannot efficiently obtain the belt grinding allowance data of a hollow blade and the application of hollow blades is limited in aviation. In this paper, a new method of obtaining belt grinding allowance data of a hollow blade based on blue light scanning was proposed according to complex surface structural characteristics of a hollow blade and surface contact characteristics of belt grinding. The point cloud information of a hollow blade was obtained through blue light there-dimensional scanning and then matched with an improved icp algorithm considering the curvature change of the hollow blade, so as to obtain the belt grinding allowance of the hollow blade. Finally, the measurement method was verified by the belt grinding experiment with the hollow blade. The experimental results confirmed that the improved icp algorithm was more accurate and that the measurement method could obtain the allowance data of the hollow blade.

关键词： Hollow blade Blue light scanning icp algorithm Belt grinding Allowance

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A frequency domain technique for range data registration

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IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE 2002年第11期24卷 1468-1484页

作者： Lucchese, L Doretto, G Cortelazzo, GM Oregon State Univ Dept Elect & Comp Engn Corvallis OR 97331 USA Univ Calif Los Angeles Dept Comp Sci Los Angeles CA 90095 USA Univ Padua Dept Elect & Informat I-35131 Padua Italy

This work introduces an original method for registering pairs of 3D views consisting of range data sets which operates in the frequency domain. The Fourier transform allows the decoupling of the estimate of the rotation parameters from the estimate of the translation parameters, our algorithm exploits this well-known property by suggesting a three-step procedure. The rotation parameters are estimated by the first two steps through convenient representations and projections of the Fourier transforms' magnitudes and the translational displacement is recovered by the third step by means of a standard phase correlation technique after compensating one of the two views for rotation. The performance of the algorithm, which is well-suited for unsupervised registration, is clearly assessed through extensive testing with several objects and shows that good and robust estimates of 3D rigid motion are achievable. Our algorithm can be used as a prealignment tool for more accurate space-domain registration techniques, like the icp algorithm.

关键词： range data 3D view registration 3D rotation Fourier transform phase correlation icp algorithm

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A high efficient multi-robot simultaneous localization and mapping system using partial computing offloading assisted cloud point registration strategy

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JOURNAL OF PARALLEL AND DISTRIBUTED COMPUTING 2021年 149卷 89-102页

作者： Li, Biwei Mi, Zhenqiang Guo, Yu Yang, Yang Obaidat, Mohammad S. Univ Sci & Technol Beijing Sch Comp & Commun Engn Beijing Peoples R China Univ Sharjah Coll Comp & Informat Founding Dean & Prof Sharjah 27272 U Arab Emirates Univ Jordan King Abdullah II Sch Informat Technol Amman 11942 Jordan Univ Sci & Technol Beijing Beijing 100083 Peoples R China

The robots using visual simultaneous localization and mapping (SLAM) system are generally experiencing excessive power consumption and suffer from depletion of battery energy during the course of working. The intensive computation necessary to complete complicated tasks is overwhelming for inexpensive mobile robots with limited on-board resources. To address this problem, a novel task offloading strategy combined with a new dense point cloud map construction method is proposed in this paper, which is firstly used for the improvement of the system especially in indoor scenes. First, we develop a novel strategy to remotely offload computation-intensive tasks to cloud center so that the tasks that could not originally be achieved locally on the resource-limited robot systems become possible. Second, a modified iterative closest point algorithm (icp), named fitness score hierarchical icp algorithm (FS-Hicp), is developed to accelerate point cloud registration. The correctness, efficiency, and scalability of the proposed strategy are evaluated with both theoretical analysis and experimental simulations. The results show that the proposed method can effectively reduce the energy consumption while increase the computation capability and speed of the multi-robot visual SLAM system, especially in indoor environment. (C) 2020 Elsevier Inc. All rights reserved.

关键词： Energy consumption Multi-robot system Computing offloading SLAM system icp algorithm

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Surface registration algorithm for rapid detection of surface thermal deformation of paraboloid antennas

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High Technology Letters 2018年第3期24卷 266-271页

作者：马开锋 Huang Guiping Hu Qingfeng He Peipei School of Resources and Environment North China University of Water Resources and Electric PowerZhengzhou 450045P.R.China Henan Engineering Laboratory of Pollution Control and Coal Chemical Resources Comprehensive Utilization Zhengzhou 451191P.R.China

In order to obtain and master the surface thermal deformation of paraboloid antennas,a fast iterative closest point( Ficp) algorithm based on design coordinate guidance is proposed,which can satisfy the demands of rapid detection for surface thermal deformation. Firstly,the basic principle of the icp algorithm for registration of a free surface is given,and the shortcomings of the icp algorithm in the registration of surface are analysed,such as its complex computation,long calculation time,low efficiency,and relatively strict initial registration position. Then an improved Ficp algorithm based on design coordinate guidance is proposed. Finally,the Ficp algorithm is applied to the fast registration test for the surface thermal deformation of a paraboloid antenna. Results indicate that the approach offers better performance with regard to fast surface registration and the algorithm is more simple,efficient,and easily realized in practical engineering application.

关键词： paraboloid antenna surface thermal deformation icp algorithm fast iterative closest point (Ficp) algorithm surface registration

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An improved Monte Carlo localization using optimized iterative closest point for mobile robots

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COGNITIVE COMPUTATION AND SYSTEMS 2022年第1期4卷 20-30页

作者： Ying, Wenjian Sun, Shiyan Naval Univ Engn Wuhan 430033 Peoples R China

This paper details a solution of fusing combination features, Iterative Closest Point (icp) and Monte Carlo algorithm, in order to solve the problem that mobile robot positioning is easy to fail in a dynamic environment. Firstly, an icp algorithm based on the maximum common combination feature is proposed to provide a more stable observation point information and therefore avoids the problem of local extremes and obtains more accurate matching results. A novel proposal distribution is then designed and auxiliary particles are used, so that the particle sets are distributed in high-observational areas closer to the true posterior probability of the state. Finally, the experimental results on the public datasets show that the proposed algorithm is more accurate in these environments.

关键词： auxiliary particles combined features icp algorithm Monte Carlo localization proposal distribution

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