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Robust Partial-to-Partial Point Cloud Registration in a Full Range [article]

Liang Pan, Zhongang Cai, Ziwei Liu
2022 arXiv   pre-print
In this work, we propose Graph Matching Consensus Network (GMCNet), which estimates pose-invariant correspondences for full-range Partial-to-Partial point cloud Registration (PPR) in the object-level registration  ...  Point cloud registration for 3D objects is a challenging task due to sparse and noisy measurements, incomplete observations and large transformations.  ...  Acknowledgments This work is supported by NTU NAP, MOE AcRF Tier 2 (T2EP20221-0033), and under the RIE2020 Industry Alignment Fund -Industry Collaboration Projects (IAF-ICP) Funding Initiative, as well as cash and in-kind  ... 
arXiv:2111.15606v2 fatcat:275xf3i3yfc6rncft6ves5luee

Point Cloud Overlapping Region Co-Segmentation Network

Kexue Fu, Xiaoyuan Luo, Manning Wang
2020 NIPS Workshop on Pre-registration in Machine Learning  
In this paper, we propose the concept of co-segmentation of the overlapping region of two 3D point clouds and develop a deep neural network to solve this problem.  ...  3D point clouds are being increasingly used in the field of computer vision and many applications involve the processing of partially overlapping point clouds.  ...  Acknowledgment This work was supported in part by the National Natural Science Foundation of China under Grant 81701795.  ... 
dblp:conf/preregister/FuLW20 fatcat:n6lmxty75ff73cx5bnab2wphwq

An Accelerated and Robust Partial Registration Algorithm for Point Clouds

Xin Wang, Xiaohuang Zhu, Shihui Ying, Chaomin Shen
2020 IEEE Access  
Unfortunately, partial registration is challenging due to difficulties such as the low overlap ratio of two point clouds and the perturbation in the orderless and sparse 3D point clouds.  ...  To overcome these problems, we introduce a parallel coarse-to-fine partial registration method.  ...  Hence, 4PCS based algorithms are relatively robust to partial registration.  ... 
doi:10.1109/access.2020.3019209 fatcat:u56qv4gajfd2bcxqqnzjhmpttq

MaskNet: A Fully-Convolutional Network to Estimate Inlier Points [article]

Vinit Sarode, Animesh Dhagat, Rangaprasad Arun Srivatsan, Nicolas Zevallos, Simon Lucey, Howie Choset
2020 arXiv   pre-print
Therefore, this paper presents a fully-convolutional neural network that identifies which points in one point cloud are most similar (inliers) to the points in another.  ...  From LIDAR sensors in autonomous cars and drones to the time of flight and stereo vision systems in our phones, point clouds are everywhere.  ...  MaskNet computes a mask giving the probabilities for each point in the full point cloud for having a similar point in the partial ones.  ... 
arXiv:2010.09185v1 fatcat:sfv5233crbbjtb44wvqfe4hlty

What Stops Learning-based 3D Registration from Working in the Real World? [article]

Zheng Dang, Lizhou Wang, Junning Qiu, Minglei Lu, Mathieu Salzmann
2021 arXiv   pre-print
Much progress has been made on the task of learning-based 3D point cloud registration, with existing methods yielding outstanding results on standard benchmarks, such as ModelNet40, even in the partial-to-partial  ...  Despite being trained only on synthetic data, our model generalizes to real data without any fine-tuning, reaching an accuracy of up to 67% on point clouds of unseen objects obtained with a commercial  ...  The models are evaluated on the partial-to-partial registration task on ModelNet40, with either a 45 • rotation range, or a full one.  ... 
arXiv:2111.10399v1 fatcat:gp6hzcviynaxxnlipqtqthfjvm

Broad-to-Narrow Registration and Identification of 3D Objects in Partially Scanned and Cluttered Point Clouds

Gerasimos Arvanitis, Evangelia Zacharaki, Libor Vasa, Konstantinos Moustakas
2021 IEEE transactions on multimedia  
The main contributions of this work are the introduction of a layered joint registration and indexing scheme of cluttered partial point clouds using a novel multi-scale saliency extraction technique to  ...  In this work, we present a methodology for identifying and registering partially-scanned and noisy 3D objects, lying in arbitrary positions in a 3D scene, with corresponding high-quality models.  ...  (a) partial scenes consisting of different models in arbitrary positions, registration results using: (b) Robust low-overlap 3-D point cloud registration approach [71] , (c) Discriminative Optimization  ... 
doi:10.1109/tmm.2021.3089838 fatcat:phfm3gxwcbft5oyjggxf3vjvqu

Multi-View Partial (MVP) Point Cloud Challenge 2021 on Completion and Registration: Methods and Results [article]

Liang Pan, Tong Wu, Zhongang Cai, Ziwei Liu, Xumin Yu, Yongming Rao, Jiwen Lu, Jie Zhou, Mingye Xu, Xiaoyuan Luo, Kexue Fu, Peng Gao (+17 others)
2021 arXiv   pre-print
Given multiple different observations, 3D reconstruction can be addressed by performing partial-to-partial point cloud registration.  ...  With a single incomplete point cloud, it becomes the partial point cloud completion problem.  ...  Robust partial-to- Proceedings of the IEEE conference on computer vision and partial point cloud registration in a full range. arXiv preprint pattern recognition, pages 1912–  ... 
arXiv:2112.12053v1 fatcat:dhbtm45zfbbchbzwv7rck3qnxm

MPCR-Net: Multiple Partial Point Clouds Registration Network Using a Global Template

Shijie Su, Chao Wang, Ke Chen, Jian Zhang, Hui Yang
2021 Applied Sciences  
In this study, we designed a novel MPCR-Net for multiple partial point cloud registration networks.  ...  the accuracy and robustness of the 3D point cloud registration.  ...  The rigid body transformation matrix parameters in the registration are estimated through TMPE-Net, and estimation results are robust to changes in data points.  ... 
doi:10.3390/app112210535 fatcat:jcztzbmtdfhpzaextjz6va34m4

DeepBBS: Deep Best Buddies for Point Cloud Registration [article]

Itan Hezroni, Amnon Drory, Raja Giryes, Shai Avidan
2021 arXiv   pre-print
These methods train a network to generate a representation that helps finding matching points in two 3D point clouds.  ...  Our experiments show improved performance compared to previous methods. In particular, our learned representation leads to an accurate registration for partial shapes and in unseen categories.  ...  To simulate a partial-to-partial registration between the shapes P and Q, a random 3D point from each point cloud is selected, and 768 nearest neighbor points are sampled.  ... 
arXiv:2110.03016v2 fatcat:ra73i66nm5gufnect2yfinb2ya

Analysis of ICP variants for the registration of partially overlapping time-of-flight range images

Robert L. Larkins, Michael J. Cree, Adrian A. Dorrington
2010 2010 25th International Conference of Image and Vision Computing New Zealand  
The relatively new full-field amplitude-modulated time-of-flight range imaging cameras present further complications to registration in the form of measurement errors due to mixed and scattered light.  ...  The iterative closest point (ICP) algorithm is one of the most commonly used methods for registering partially overlapping range images.  ...  Acknowledgements Robert Larkins acknowledges the financial support provided by both the Range Imaging and Waikato Doctoral Scholarships.  ... 
doi:10.1109/ivcnz.2010.6148869 fatcat:45735dlqtndxppf5opfsem3puu

Self-supervised Point Cloud Registration with Deep Versatile Descriptors [article]

Dongrui Liu, Chuanchuan Chen, Changqing Xu, Robert Qiu, Lei Chu
2022 arXiv   pre-print
The DVD is motivated by a key observation that the local distinctive geometric structures of the point cloud by two subset points can be employed to enhance the representation ability of the feature extraction  ...  Recent years have witnessed an increasing trend toward solving point cloud registration problems with various deep learning-based algorithms.  ...  PRNet [38] uses a keypoint detector to establish keypoint correspondences to solve the partial to partial point cloud registration in a self-supervised way.  ... 
arXiv:2201.10034v1 fatcat:s5oy23qh5jhj3bzhefn7gl3y7i

Best Buddies Registration for Point Clouds [article]

Amnon Drory, Tal Shomer, Shai Avidan, Raja Giryes
2020 arXiv   pre-print
We propose new, and robust, loss functions for the point cloud registration problem.  ...  This measure has been shown to be robust to outliers and missing data in the case of template matching for images.  ...  [8] later extended ICP to a full plane-to-plane formulation and gave it a probabilistic interpretation. Jian and Vemuri [9] proposed a robust point set registration.  ... 
arXiv:2010.01912v1 fatcat:t3rpaqwzsvdyhfjxvimyu3bi2m

Object Modelling with a Handheld RGB-D Camera [article]

Aitor Aldoma, Johann Prankl, Alexander Svejda, Markus Vincze
2015 arXiv   pre-print
This is achieved by acquiring several partial 3D models in different sessions that are automatically merged together to reconstruct a full model.  ...  A major advantage of the method is that our reconstruction pipeline allows the user to acquire a full 3D model of the object.  ...  Acknowledgments The research leading to these results has received funding from the European Community Seventh Framework Programme  ... 
arXiv:1505.05643v1 fatcat:7qyxne6gvbhetia2ottvudwxvu

PointNetLK: Robust & Efficient Point Cloud Registration using PointNet [article]

Yasuhiro Aoki, Hunter Goforth, Rangaprasad Arun Srivatsan, Simon Lucey
2019 arXiv   pre-print
To date, the successful application of PointNet to point cloud registration has remained elusive. In this paper we argue that PointNet itself can be thought of as a learnable "imaging" function.  ...  point cloud registration.  ...  We argue that PointNetLK is quite competitive in efficiency among current approaches to point cloud registration, due to the fact that it has complexity O(n) in n number of points.  ... 
arXiv:1903.05711v2 fatcat:3honraepobf2no7i5f5gmjv2za

End-to-end Learning the Partial Permutation Matrix for Robust 3D Point Cloud Registration [article]

Zhiyuan Zhang, Jiadai Sun, Yuchao Dai, Dingfu Zhou, Xibin Song, Mingyi He
2022 arXiv   pre-print
Even though considerable progress has been made in deep learning-based 3D point cloud processing, how to obtain accurate correspondences for robust registration remains a major challenge because existing  ...  Extensive experiments have validated our method, which creates a new state-of-the-art performance for robust 3D point cloud registration. The code will be made public.  ...  performance in robust 3D point cloud registration.  ... 
arXiv:2110.15250v2 fatcat:syuqips6mjf23eqkhpqxqrzzde
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