Rapid 3D registration using local subtree caching in iterative closest point (ICP) algorithm

2017 ◽  
Author(s):  
Ryan Uhlenbrock ◽  
Kyungnam Kim ◽  
Heiko Hoffmann ◽  
Jean J. Dolne
Keyword(s):  
Iterative Closest Point ◽  
3D Registration ◽  
Icp Algorithm

scholarly journals Estimating intrafraction tumor motion during fiducial-based liver stereotactic radiotherapy via an iterative closest point (ICP) algorithm

2019 ◽  
Vol 14 (1) ◽  
Author(s):  
Wu-zhou Li ◽  
Zhi-wen Liang ◽  
Yi Cao ◽  
Ting-ting Cao ◽  
Hong Quan ◽  
...  
Keyword(s):  
Stereotactic Radiotherapy ◽  
Imaging System ◽  
Liver Tumors ◽  
Three Dimensional ◽  
Rigid Motion ◽  
Iterative Closest Point ◽  
Tumor Motion ◽  
Tracking Accuracy ◽  
Icp Algorithm ◽  
Anterior Posterior

Abstract Background Tumor motion may compromise the accuracy of liver stereotactic radiotherapy. In order to carry out a precise planning, estimating liver tumor motion during radiotherapy has received a lot of attention. Previous approach may have difficult to deal with image data corrupted by noise. The iterative closest point (ICP) algorithm is widely used for estimating the rigid registration of three-dimensional point sets when these data were dense or corrupted. In the light of this, our study estimated the three-dimensional (3D) rigid motion of liver tumors during stereotactic liver radiotherapy using reconstructed 3D coordinates of fiducials based on the ICP algorithm. Methods Four hundred ninety-five pairs of orthogonal kilovoltage (KV) images from the CyberKnife stereo imaging system for 12 patients were used in this study. For each pair of images, the 3D coordinates of fiducial markers inside the liver were calculated via geometric derivations. The 3D coordinates were used to calculate the real-time translational and rotational motion of liver tumors around three axes via an ICP algorithm. The residual error was also investigated both with and without rotational correction. Results The translational shifts of liver tumors in left-right (LR), anterior-posterior (AP),and superior-inferior (SI) directions were 2.92 ± 1.98 mm, 5.54 ± 3.12 mm, and 16.22 ± 5.86 mm, respectively; the rotational angles in left-right (LR), anterior-posterior (AP), and superior-inferior (SI) directions were 3.95° ± 3.08°, 4.93° ± 2.90°, and 4.09° ± 1.99°, respectively. Rotational correction decreased 3D fiducial displacement from 1.19 ± 0.35 mm to 0.65 ± 0.24 mm (P<0.001). Conclusions The maximum translational movement occurred in the SI direction. Rotational correction decreased fiducial displacements and increased tumor tracking accuracy.

scholarly journals OICP: An Online Fast Registration Algorithm Based on Rigid Translation Applied to Wire Arc Additive Manufacturing of Mold Repair

Materials ◽  
2021 ◽  
Vol 14 (6) ◽  
pp. 1563
Author(s):  
Ruibing Wu ◽  
Ziping Yu ◽  
Donghong Ding ◽  
Qinghua Lu ◽  
Zengxi Pan ◽  
...  
Keyword(s):  
Additive Manufacturing ◽  
Point Cloud ◽  
Point Clouds ◽  
Iterative Closest Point ◽  
Multiple Point ◽  
Icp Algorithm ◽  
Registration Algorithm ◽  
Cloud Models ◽  
Comparison Results ◽  
Wire Arc Additive Manufacturing

As promising technology with low requirements and high depositing efficiency, Wire Arc Additive Manufacturing (WAAM) can significantly reduce the repair cost and improve the formation quality of molds. To further improve the accuracy of WAAM in repairing molds, the point cloud model that expresses the spatial distribution and surface characteristics of the mold is proposed. Since the mold has a large size, it is necessary to be scanned multiple times, resulting in multiple point cloud models. The point cloud registration, such as the Iterative Closest Point (ICP) algorithm, then plays the role of merging multiple point cloud models to reconstruct a complete data model. However, using the ICP algorithm to merge large point clouds with a low-overlap area is inefficient, time-consuming, and unsatisfactory. Therefore, this paper provides the improved Offset Iterative Closest Point (OICP) algorithm, which is an online fast registration algorithm suitable for intelligent WAAM mold repair technology. The practicality and reliability of the algorithm are illustrated by the comparison results with the standard ICP algorithm and the three-coordinate measuring instrument in the Experimental Setup Section. The results are that the OICP algorithm is feasible for registrations with low overlap rates. For an overlap rate lower than 60% in our experiments, the traditional ICP algorithm failed, while the Root Mean Square (RMS) error reached 0.1 mm, and the rotation error was within 0.5 degrees, indicating the improvement of the proposed OICP algorithm.

scholarly journals Rigid Shape Registration Based on Extended Hamiltonian Learning

Entropy ◽  
2020 ◽  
Vol 22 (5) ◽  
pp. 539
Author(s):  
Jin Yi ◽  
Shiqiang Zhang ◽  
Yueqi Cao ◽  
Erchuan Zhang ◽  
Huafei Sun
Keyword(s):  
Image Analysis ◽  
Optimization Problem ◽  
Iterative Closest Point ◽  
Euclidean Group ◽  
Simulation Experiments ◽  
Icp Algorithm ◽  
Registration Error ◽  
Shape Registration ◽  
Correct Alignment ◽  
State Of Art

Shape registration, finding the correct alignment of two sets of data, plays a significant role in computer vision such as objection recognition and image analysis. The iterative closest point (ICP) algorithm is one of well known and widely used algorithms in this area. The main purpose of this paper is to incorporate ICP with the fast convergent extended Hamiltonian learning (EHL), so called EHL-ICP algorithm, to perform planar and spatial rigid shape registration. By treating the registration error as the potential for the extended Hamiltonian system, the rigid shape registration is modelled as an optimization problem on the special Euclidean group S E ( n ) ( n = 2 , 3 ) . Our method is robust to initial values and parameters. Compared with some state-of-art methods, our approach shows better efficiency and accuracy by simulation experiments.

WTG’s Gearbox Condition Assessment by Matching the Hilbert-Huang Spectrum of Vibration Signal

2013 ◽  
Vol 291-294 ◽  
pp. 522-526
Author(s):  
Hai Ning Pan ◽  
Ming Qin ◽  
Lei Pan
Keyword(s):  
Vibration Signal ◽  
Condition Assessment ◽  
Assessment Method ◽  
Iterative Closest Point ◽  
Intrinsic Mode Functions ◽  
Turbine Generator ◽  
Vibration Signals ◽  
Icp Algorithm ◽  
Wind Turbine Generator ◽  
Mode Decomposition

A gearbox condition assessment method for the Wind Turbine Generator (WTG) is proposed. Vibration signal’s Intrinsic Mode Functions (IMF) are decomposed by Empirical Mode Decomposition (EMD). Normalized Hilbert-Huang and Direct Quadrature (DQ) method are used to determine the instantaneous frequency. The HHS of vibration signals is plotted and then is shifted to match the pre-defined faulty gear condition by the Iterative Closest Point (ICP) algorithm to diagnose their similarities. The principle and effectiveness of the proposed method are illustrated by simulation, the fault types of gearbox can be identified by ICP algorithm effectively.

scholarly journals BASED ON GPU FOR STRIP ADJUSTMENT ALGORITHM OF LIDAR DATA

2020 ◽  
Vol XLII-3/W10 ◽  
pp. 229-233
Author(s):  
B. Song ◽  
G. Q. Zhou ◽  
Y. L. Lu ◽  
X. Zhou ◽  
P. Liang
Keyword(s):  
Iterative Closest Point ◽  
Lidar Data ◽  
Icp Algorithm ◽  
Nearest Point ◽  
Adjustment Speed ◽  
Data Volume ◽  
Data Error

Abstract. In order to solve the problem that the source of LiDAR data error needs to be adjusted and the data volume is large, the adjustment speed between the voyages is slow and cannot be automatically adjusted. Based on the iterative nearest point (ICP) algorithm, this paper proposes an improved iterative closest point (ICP) algorithm based on GPU parallel octree. The algorithm quickly constructs the octree of LiDAR nautical belt data in the GPU, uses the octree to quickly find the overlapping area of the nautical band, and then uses the ICP algorithm in the overlapping area to solve the adjustment parameters R and T quickly. Then the entire flight belt is quickly adjusted. Experiments with example data show that this method can quickly and automatically adjustment a large number of LiDAR data, and the adjustment precision can meet the precision requirements of the production.

Considerations of form defects and surface deformations for tolerance analysis of cylindrical components

2021 ◽  
pp. 095440542199141
Author(s):  
Zhiqiang Zhang ◽  
Jianhua Liu ◽  
Laurent Pierre ◽  
Nabil Anwer
Keyword(s):  
Tolerance Analysis ◽  
Iterative Closest Point ◽  
Simulation Methods ◽  
Skin Model ◽  
Icp Algorithm ◽  
Surface Deformations ◽  
Research Outcomes ◽  
Considerable Research ◽  
Computer Aided ◽  
External Forces

The modeling and simulation of cylindrical surfaces with consideration of form defects have led to considerable research outcomes in the field of Computer-Aided Tolerancing (CAT). However, further consideration of surface deformations caused by external forces still remains a challenge. To address this issue, this paper properly considers the form defects and surface deformations for tolerance analysis of cylindrical components. First, form defects are considered by modeling skin model shapes of cylindrical surfaces. Afterwards, the tight fit and loose fit of a pair of cylindrical surfaces are identified, and the simulation methods of their positioning are presented. Specifically, for tight fit situation, a k-d tree based Iterative Closest Point (ICP) algorithm is used, and for loose fit situation, the constrained registration approach is adopted. Moreover, a Conjugate Gradient-Fast Fourier Transform (CG-FFT) method is presented for the consideration of surface deformations. In addition, simulations of given examples are conducted, which show the considerable effects of form defects and surface deformations. The simulations may also help determine the best performance of the to-be-assembled cylindrical components.

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