scholarly journals A Robust Nonrigid Point Set Registration Method Based on Collaborative Correspondences

Sensors ◽  
2020 ◽  
Vol 20 (11) ◽  
pp. 3248
Author(s):  
Xiang-Wei Feng ◽  
Da-Zheng Feng
Keyword(s):  
Video Processing ◽  
Heuristic Method ◽  
Spatial Location ◽  
Structural Features ◽  
Registration Method ◽  
Point Set Registration ◽  
Closed Form Solutions ◽  
Point Set ◽  
Point To Point ◽  
And Control

The nonrigid point set registration is one of the bottlenecks and has the wide applications in computer vision, pattern recognition, image fusion, video processing, and so on. In a nonrigid point set registration problem, finding the point-to-point correspondences is challengeable because of the various image degradations. In this paper, a robust method is proposed to accurately determine the correspondences by fusing the two complementary structural features, including the spatial location of a point and the local structure around it. The former is used to define the absolute distance (AD), and the latter is exploited to define the relative distance (RD). The AD-correspondences and the RD-correspondences can be established based on AD and RD, respectively. The neighboring corresponding consistency is employed to assign the confidence for each RD-correspondence. The proposed heuristic method combines the AD-correspondences and the RD-correspondences to determine the corresponding relationship between two point sets, which can significantly improve the corresponding accuracy. Subsequently, the thin plate spline (TPS) is employed as the transformation function. At each step, the closed-form solutions of the affine and nonaffine parts of TPS can be independently and robustly solved. It facilitates to analyze and control the registration process. Experimental results demonstrate that our method can achieve better performance than several existing state-of-the-art methods.

A robust non-rigid point set registration method based on inhomogeneous Gaussian mixture models

2017 ◽  
Vol 34 (10) ◽  
pp. 1399-1414 ◽  
Author(s):  
Wanxia Deng ◽  
Huanxin Zou ◽  
Fang Guo ◽  
Lin Lei ◽  
Shilin Zhou ◽  
...  
Keyword(s):  
Mixture Models ◽  
Gaussian Mixture Models ◽  
Gaussian Mixture ◽  
Registration Method ◽  
Point Set Registration ◽  
Point Set

Point set registration for assembly feature pose estimation using simulated annealing nested Gauss-Newton optimization

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Kunyong Chen ◽  
Yong Zhao ◽  
Jiaxiang Wang ◽  
Hongwen Xing ◽  
Zhengjian Dong
Keyword(s):  
Simulated Annealing ◽  
Pose Estimation ◽  
Distance Metric ◽  
Implicit Representation ◽  
Registration Method ◽  
Content Type ◽  
Point Set Registration ◽  
Searching Strategy ◽  
Global Robustness ◽  
Point Set

Purpose This paper aims to propose a fast and robust 3D point set registration method for pose estimation of assembly features with few distinctive local features in the manufacturing process. Design/methodology/approach The distance between the two 3D objects is analytically approximated by the implicit representation of the target model. Specifically, the implicit B-spline surface is adopted as an interface to derive the distance metric. With the distance metric, the point set registration problem is formulated into an unconstrained nonlinear least-squares optimization problem. Simulated annealing nested Gauss-Newton method is designed to solve the non-convex problem. This integration of gradient-based optimization and heuristic searching strategy guarantees both global robustness and sufficient efficiency. Findings The proposed method improves the registration efficiency while maintaining high accuracy compared with several commonly used approaches. Convergence can be guaranteed even with critical initial poses or in partial overlapping conditions. The multiple flanges pose estimation experiment validates the effectiveness of the proposed method in real-world applications. Originality/value The proposed registration method is much more efficient because no feature estimation or point-wise correspondences update are performed. At each iteration of the Gauss–Newton optimization, the poses are updated in a singularity-free format without taking the derivatives of a bunch of scalar trigonometric functions. The advantage of the simulated annealing searching strategy is combined to improve global robustness. The implementation is relatively straightforward, which can be easily integrated to realize automatic pose estimation to guide the assembly process.

Robust point set registration method based on global structure and local constraints

2019 ◽  
Vol 5 (2) ◽  
pp. 76
Author(s):  
Yufei Chen ◽  
Kai Yang ◽  
Haotian Zhang ◽  
Xianhui Liu ◽  
Weidong Zhao
Keyword(s):  
Global Structure ◽  
Local Constraints ◽  
Registration Method ◽  
Point Set Registration ◽  
Point Set

scholarly journals GO-APSR: A Globally Optimal Affine Point Set Registration Method

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 137232-137240 ◽  
Author(s):  
Xuechen Li ◽  
Yinlong Liu ◽  
Manning Wang ◽  
Zhijian Song
Keyword(s):  
Registration Method ◽  
Point Set Registration ◽  
Point Set

scholarly journals Robust non‐rigid point set registration method based on asymmetric Gaussian and structural feature

2018 ◽  
Vol 12 (6) ◽  
pp. 806-816 ◽  
Author(s):  
Jun Dou ◽  
Dongmei Niu ◽  
Zhiquan Feng ◽  
Xiuyang Zhao
Keyword(s):  
Structural Feature ◽  
Registration Method ◽  
Point Set Registration ◽  
Point Set

Integration of affine ICP into the precise localization problem of smart-AGVs: Procedures, enhancements and challenges

2020 ◽  
pp. 014233122093343
Author(s):  
Abdurrahman Yilmaz ◽  
Hakan Temeltas
Keyword(s):  
Indoor Environments ◽  
Precise Localization ◽  
Localization Problem ◽  
Point Sets ◽  
Registration Method ◽  
Point Set Registration ◽  
Rotation Plane ◽  
Point Set ◽  
Localization Performance ◽  
Industrial Standards

The localization problem in robotics has been widely studied both for indoor and outdoor applications, but is still open for improvements. In indoor environments, GPS-based methods are not preferred due to reflections, and the pose of the robot is determined according to the measurements taken around with its sensors. One of them is iterative closest point (ICP)-based localization method. ICP is a point set registration method, the essence of which is to iteratively compute the transformation between two point sets. However, it is also utilized to solve the localization problem thanks to its high precision in registration. Precise localization is important for applications that require highly accurate pose estimation, such as for smart-AGVs to be used in smart factories to reach a station at industrial standards. Traditional ICP finds transformation in terms of a rotation and translation, and thus can be directly applied to the localization problem. On the other hand, the affine variant of ICP is not adapted to solve the localization problem. In this study, the necessary arrangements to make affine ICP suitable for precise localization are given as a procedure such that the transformation between point sets is found by affine ICP, the resulting transformation is projected to rotation plane by polar decomposition and then the pose is estimated. The enhancements achieved with the usage of affine ICP in precise localization problems are demonstrated in simulation by comparing localization performance of affine ICP with that of traditional ICP. For this purpose, in a factory environment, a scenario where a smart-AGV approaching the target autonomously to carry out an operation has been prepared. The performances of the algorithms have been evaluated for five different docking stations with 30 separate experiments. Moreover, the challenges related to the affine ICP-based fine localization, in particular about finding projection of affine transformation to rotation plane, are highlighted in this study.

Interference mitigation in point to point wireless sensor networks using LSP protocol and time division multiplexing approach

2020 ◽  
Vol 39 (4) ◽  
pp. 5449-5458
Author(s):  
A. Arokiaraj Jovith ◽  
S.V. Kasmir Raja ◽  
A. Razia Sulthana
Keyword(s):  
Energy Consumption ◽  
Large Scale ◽  
Control Parameter ◽  
Interference Mitigation ◽  
Wireless Sensor ◽  
Point To Point ◽  
A Minor ◽  
Two Stages ◽  
Time Division ◽  
And Control

Interference in Wireless Sensor Network (WSN) predominantly affects the performance of the WSN. Energy consumption in WSN is one of the greatest concerns in the current generation. This work presents an approach for interference measurement and interference mitigation in point to point network. The nodes are distributed in the network and interference is measured by grouping the nodes in the region of a specific diameter. Hence this approach is scalable and isextended to large scale WSN. Interference is measured in two stages. In the first stage, interference is overcome by allocating time slots to the node stations in Time Division Multiple Access (TDMA) fashion. The node area is split into larger regions and smaller regions. The time slots are allocated to smaller regions in TDMA fashion. A TDMA based time slot allocation algorithm is proposed in this paper to enable reuse of timeslots with minimal interference between smaller regions. In the second stage, the network density and control parameter is introduced to reduce interference in a minor level within smaller node regions. The algorithm issimulated and the system is tested with varying control parameter. The node-level interference and the energy dissipation at nodes are captured by varying the node density of the network. The results indicate that the proposed approach measures the interference and mitigates with minimal energy consumption at nodes and with less overhead transmission.

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