Rigid Transformation Estimation

2021 ◽  
pp. 1099-1099
Keyword(s):  
Rigid Transformation

scholarly journals V4PCS: Volumetric 4PCS Algorithm for Global Registration

2017 ◽  
Author(s):  
Jida Huang ◽  
Tsz-Ho Kwok ◽  
Chi Zhou
Keyword(s):  
Mass Customization ◽  
Process Development ◽  
Three Dimensional ◽  
Rigid Transformation ◽  
New Paradigm ◽  
Shape Registration ◽  
Related Data ◽  
Global Registration ◽  
Information Reuse ◽  
Customized Products

With the advances in hardware and process development, additive manufacturing is realizing a new paradigm: mass customization. There are massive human-related data in mass customization, but there are also many similarities in mass-customized products. Therefore, reusing information can facilitate mass customization and create unprecedented opportunities in advancing the theory, method, and practice of design for mass-customized products. To enable information reuse, different models have to be aligned so that their similarity can be identified. This alignment is commonly known as the global registration that finds an optimal rigid transformation to align two three-dimensional shapes (scene and model) without any assumptions on their initial positions. The Super 4-Points Congruent Sets (S4PCS) is a popular algorithm used for this shape registration. While S4PCS performs the registration using a set of 4 coplanar points, we find that incorporating the volumetric information of the models can improve the robustness and the efficiency of the algorithm, which are particularly important for mass customization. In this paper, we propose a novel algorithm, Volumetric 4PCS (V4PCS), to extend the 4 coplanar points to non-coplanar ones for global registration, and theoretically demonstrate the computational complexity is significantly reduced. Several typical human-centered applications such as tooth aligner and hearing aid are investigated and compared with S4PCS. The experimental results show that the proposed V4PCS can achieve a maximum of 20 times speedup and can successfully compute the valid transformation with very limited number of sample points.

scholarly journals Simultaneous Robot–World and Hand–Eye Calibration without a Calibration Object

Sensors ◽  
2018 ◽  
Vol 18 (11) ◽  
pp. 3949 ◽  
Author(s):  
Wei Li ◽  
Mingli Dong ◽  
Naiguang Lu ◽  
Xiaoping Lou ◽  
Peng Sun
Keyword(s):  
Three Dimensional ◽  
Real Data ◽  
Medical Robotics ◽  
Calibration Method ◽  
Bundle Adjustment ◽  
Data Sets ◽  
Rigid Transformation ◽  
Validation Experiment ◽  
Dimensional Reconstruction ◽  
Sparse Bundle Adjustment

An extended robot–world and hand–eye calibration method is proposed in this paper to evaluate the transformation relationship between the camera and robot device. This approach could be performed for mobile or medical robotics applications, where precise, expensive, or unsterile calibration objects, or enough movement space, cannot be made available at the work site. Firstly, a mathematical model is established to formulate the robot-gripper-to-camera rigid transformation and robot-base-to-world rigid transformation using the Kronecker product. Subsequently, a sparse bundle adjustment is introduced for the optimization of robot–world and hand–eye calibration, as well as reconstruction results. Finally, a validation experiment including two kinds of real data sets is designed to demonstrate the effectiveness and accuracy of the proposed approach. The translation relative error of rigid transformation is less than 8/10,000 by a Denso robot in a movement range of 1.3 m × 1.3 m × 1.2 m. The distance measurement mean error after three-dimensional reconstruction is 0.13 mm.

Parallel calibration based on modified trim strategy

2019 ◽  
Vol 40 (2) ◽  
pp. 249-256
Author(s):  
Yaxin Peng ◽  
Naiwu Wen ◽  
Chaomin Shen ◽  
Xiaohuang Zhu ◽  
Shihui Ying
Keyword(s):  
Computation Time ◽  
Extraction Methods ◽  
Intelligent Manufacturing ◽  
Feature Descriptor ◽  
Data Sets ◽  
Rigid Transformation ◽  
Robot Calibration ◽  
Content Type ◽  
Partial Alignment ◽  
Point Set

Purpose Partial alignment for 3 D point sets is a challenging problem for laser calibration and robot calibration due to the unbalance of data sets, especially when the overlap of data sets is low. Geometric features can promote the accuracy of alignment. However, the corresponding feature extraction methods are time consuming. The purpose of this paper is to find a framework for partial alignment by an adaptive trimmed strategy. Design/methodology/approach First, the authors propose an adaptive trimmed strategy based on point feature histograms (PFH) coding. Second, they obtain an initial transformation based on this partition, which improves the accuracy of the normal direction weighted trimmed iterative closest point (ICP) method. Third, they conduct a series of GPU parallel implementations for time efficiency. Findings The initial partition based on PFH feature improves the accuracy of the partial registration significantly. Moreover, the parallel GPU algorithms accelerate the alignment process. Research limitations/implications This study is applicable to rigid transformation so far. It could be extended to non-rigid transformation. Practical implications In practice, point set alignment for calibration is a technique widely used in the fields of aircraft assembly, industry examination, simultaneous localization and mapping and surgery navigation. Social implications Point set calibration is a building block in the field of intelligent manufacturing. Originality/value The contributions are as follows: first, the authors introduce a novel coarse alignment as an initial calibration by PFH descriptor similarity, which can be viewed as a coarse trimmed process by partitioning the data to the almost overlap part and the rest part; second, they reduce the computation time by GPU parallel coding during the acquisition of feature descriptor; finally, they use the weighted trimmed ICP method to refine the transformation.

scholarly journals V4PCS: Volumetric 4PCS Algorithm for Global Registration

2017 ◽  
Vol 139 (11) ◽  
Author(s):  
Jida Huang ◽  
Tsz-Ho Kwok ◽  
Chi Zhou
Keyword(s):  
Mass Customization ◽  
Three Dimensional ◽  
Experimental Tests ◽  
Data Driven ◽  
Rigid Transformation ◽  
Shape Registration ◽  
Related Data ◽  
Global Registration ◽  
Information Reuse ◽  
3D Shapes

With the advances in three-dimensional (3D) scanning and sensing technologies, massive human-related data are now available and create many applications in data-driven design. Similarity identification is one of the basic problems in data-driven design and can facilitate many engineering applications and product paradigm such as quality control and mass customization. Therefore, reusing information can create unprecedented opportunities in advancing the theory, method, and practice of product design. To enable information reuse, different models must be aligned so that their similarity can be identified. This alignment is commonly known as the global registration that finds an optimal rigid transformation to align two 3D shapes (scene and model) without any assumptions on their initial positions. The Super 4-Points Congruent Sets (S4PCS) is a popular algorithm used for this shape registration. While S4PCS performs the registration using a set of four coplanar points, we find that incorporating the volumetric information of the models can improve the robustness and the efficiency of the algorithm, which are particularly important for mass customization. In this paper, we propose a novel algorithm, Volumetric 4PCS (V4PCS), to extend the four coplanar points to noncoplanar ones for global registration, and theoretically demonstrate the computational complexity is significantly reduced. Experimental tests are conducted on several models such as tooth aligner and hearing aid to compare with S4PCS. The experimental results show that the proposed V4PCS can achieve a maximum of 20 times speedup and can successfully compute the valid transformation with very limited number of sample points. An application of the proposed method in mass customization is also investigated.

scholarly journals TIF-Reg: Point Cloud Registration with Transform-Invariant Features in SE(3)

Sensors ◽  
2021 ◽  
Vol 21 (17) ◽  
pp. 5778
Author(s):  
Baifan Chen ◽  
Hong Chen ◽  
Baojun Song ◽  
Grace Gong
Keyword(s):  
Feature Extraction ◽  
Point Cloud ◽  
Point Clouds ◽  
Rigid Transformation ◽  
Point Cloud Registration ◽  
Registration Method ◽  
Invariant Features ◽  
Invariant Feature ◽  
Deep Feature ◽  
Wide Range

Three-dimensional point cloud registration (PCReg) has a wide range of applications in computer vision, 3D reconstruction and medical fields. Although numerous advances have been achieved in the field of point cloud registration in recent years, large-scale rigid transformation is a problem that most algorithms still cannot effectively handle. To solve this problem, we propose a point cloud registration method based on learning and transform-invariant features (TIF-Reg). Our algorithm includes four modules, which are the transform-invariant feature extraction module, deep feature embedding module, corresponding point generation module and decoupled singular value decomposition (SVD) module. In the transform-invariant feature extraction module, we design TIF in SE(3) (which means the 3D rigid transformation space) which contains a triangular feature and local density feature for points. It fully exploits the transformation invariance of point clouds, making the algorithm highly robust to rigid transformation. The deep feature embedding module embeds TIF into a high-dimension space using a deep neural network, further improving the expression ability of features. The corresponding point cloud is generated using an attention mechanism in the corresponding point generation module, and the final transformation for registration is calculated in the decoupled SVD module. In an experiment, we first train and evaluate the TIF-Reg method on the ModelNet40 dataset. The results show that our method keeps the root mean squared error (RMSE) of rotation within 0.5∘ and the RMSE of translation error close to 0 m, even when the rotation is up to [−180∘, 180∘] or the translation is up to [−20 m, 20 m]. We also test the generalization of our method on the TUM3D dataset using the model trained on Modelnet40. The results show that our method’s errors are close to the experimental results on Modelnet40, which verifies the good generalization ability of our method. All experiments prove that the proposed method is superior to state-of-the-art PCReg algorithms in terms of accuracy and complexity.

scholarly journals Water Droplet Morphing Combining Rigid Transformation

2005 ◽  
pp. 671-678 ◽  
Author(s):  
Lanfen Lin ◽  
Shenghui Liao ◽  
RuoFeng Tong ◽  
JinXiang Dong
Keyword(s):  
Water Droplet ◽  
Rigid Transformation

scholarly journals Investigations on the Coregistration of Sentinel-1 TOPS with the Conventional Cross-Correlation Technique

2018 ◽  
Vol 10 (9) ◽  
pp. 1405 ◽  
Author(s):  
Yuxiao Qin ◽  
Daniele Perissin ◽  
Jing Bai
Keyword(s):  
Cross Correlation ◽  
Phase Error ◽  
Impulse Response Function ◽  
Correlation Method ◽  
Correlation Technique ◽  
Geometrical Approach ◽  
Rigid Transformation ◽  
Interferometric Phase ◽  
The Cross ◽  
Cross Correlation Technique

In Sentinel-1 TOPS mode, the antenna sweeps in the azimuth direction for the purpose of illuminating the targets with the entire azimuth antenna pattern (AAP). This azimuth sweeping introduces an extra high-frequency Doppler term into the impulse response function (IRF), which poses a more strict coregistration accuracy for the interferometric purpose. A 1/1000 pixel coregistration accuracy is required for the interferometric phase error to be negligible, and the enhanced spectral diversity (ESD) method is applied for achieving such accuracy. However, since ESD derives miscoregistration from cross-interferometric phase, and phase is always wrapped to [ − π , π ) , an initial coregistration method with enough accuracy is required to resolve the phase ambiguity in ESD. The mainstream for initial coregistration that meets this requirement is the geometrical approach, which accuracy mainly depends on the accuracy of orbits. In this article, the authors propose to investigate the feasibility of using the conventional coregistration approach, namely the cross-correlation-and-rigid-transformation, as the initial coregistration method. The aim is to quantify the coregistration accuracy for cross-correlation-and-rigid-transformation using the Cramér-Rao lower bound (CRLB) and determine whether this method could eventually help to resolve the phase ambiguities of ESD. In addition, we studied the feasibility and robustness of the cross-correlation plus ESD under different conditions. For validation, we checked whether the cross-correlation plus ESD approach could reach the same coregistration accuracy as geometrical plus ESD approach. In general, for large areas with enough coherence and little topography variance, the cross-correlation method could be used as an alternative to the geometrical approach. The interferogram from the two different approaches (with ESD applied afterward) shows a negligible difference under such circumstances.

Sign in / Sign up

Export Citation Format

Share Document