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A Robust Rigid Registration Framework of 3D Indoor Scene Point Clouds Based on RGB-D Information

Saishang Zhong, Mingqiang Guo, Ruina Lv, Jianguo Chen, Zhong Xie, Zheng Liu
2021 Remote Sensing  
To solve the problem, we present a point cloud registration framework in view of RGB-D information.  ...  Nevertheless, state-of-the-art registration approaches still have defects when dealing with low-quality indoor scene point clouds derived from consumer-grade RGB-D sensors.  ...  The key idea is to fully utilize texture and geometry information computed from RGB-D images to build correspondences between point clouds accurately.  ... 
doi:10.3390/rs13234755 fatcat:4z2bol6n6fazjd2cp4q7ipzgp4

The 3D Point Clouds Registration for Human Foot [chapter]

Yi Xie, Xiuqin Shang, Yuqing Li, Xiwei Liu, Fenghua Zhu, Gang Xiong, Susanna Pirttikangas, Jiehan Zhou
2018 IFIP Advances in Information and Communication Technology  
Dealing with the customized footwear, we choose a novel algorithm, which combines the NARF key point detector and the FPFH descriptor, to improve the efficiency of the initial iteration and reduce the  ...  In the experiment, we get the point clouds of the human foot from the Artec 3D scanner and complete the registration of the point clouds from different visual angles.  ...  Use the Normal Aligned Radial Feature (NARF) algorithm to extract key points from the point cloud. 3. Put each key point on the origin and create a partial reference system.  ... 
doi:10.1007/978-3-030-01313-4_30 fatcat:eutnetwm7reeda6wiarntdfwha

On-the-Fly Camera and Lidar Calibration

Balázs Nagy, Csaba Benedek
2020 Remote Sensing  
We adopt a structure from motion (SfM) method to generate 3D point clouds from the camera data which can be matched to the Lidar point clouds; thus, we address the extrinsic calibration problem as a registration  ...  Thereafter, we apply a control point based nonrigid transformation refinement step to register the point clouds more precisely.  ...  In order to find the optimal matching, we use the extracted two sets of object centroids from the SfM-based and the Lidar point clouds, respectively, and we search for an optimal rigid transform, T 2 of  ... 
doi:10.3390/rs12071137 fatcat:ay4yvbo7jbar3dg6gnsbecxvvu

A G-Super4PCS Registration Method for Photogrammetric and TLS Data in Geology

Rongchun Zhang, Hao Li, Lanfa Liu, Mingfei Wu
2017 ISPRS International Journal of Geo-Information  
This paper presents a Generalized Super 4-points Congruent Sets (G-Super4PCS) algorithm to register the TLS point cloud as well as Structure from Motion (SfM) point cloud generated from disordered digital  ...  The G-Super4PCS algorithm mainly includes three stages: (1) key-scale rough estimation for point clouds; (2) extraction for the generalized super 4-points congruent base set and scale adaptive optimization  ...  We would like to thank all the anonymous reviewers who provided useful comments, which were incorporated into this manuscript.  ... 
doi:10.3390/ijgi6050129 fatcat:bjnl76lv3ravdfvmeznqw6joca

A Systematic Approach for Cross-Source Point Cloud Registration by Preserving Macro and Micro Structures

Xiaoshui Huang, Jian Zhang, Lixin Fan, Qiang Wu, Chun Yuan
2017 IEEE Transactions on Image Processing  
Our work has three main contributions: (1) a systematic pipeline to deal with cross-source point cloud registration; (2) a graph construction method to maintain macro and micro structures; (3) a new graph  ...  We propose a systematic approach for registering cross-source point clouds.  ...  ACKNOWLEDGMENT The authors would like to thank the Nokia Corporation for their help and acknowledge the useful discussions with colleagues in GBDTC.  ... 
doi:10.1109/tip.2017.2695888 pmid:28436871 fatcat:ukciy4ot3re4pipymaolhzi4oe

Numerical methods for polyline-to-point-cloud registration with applications to patient-specific stent reconstruction

Claire Yilin Lin, Alessandro Veneziani, Lars Ruthotto
2017 International Journal for Numerical Methods in Biomedical Engineering  
Given a point cloud of strut positions, which can be extracted from images, our stent reconstruction method aims at finding a geometrical transformation that aligns a model of the undeployed stent to the  ...  In fact, the undeployed stent is registered to the point cloud of strut locations using a non-rigid point-to-point registration procedure [29] .  ...  Boyi Yang for his help in preparing the data set and invaluable feedback as well as the Core Lab in the Interventional Cardiology of the Emory University Hospital (H. Samady, B.  ... 
doi:10.1002/cnm.2934 pmid:29073332 fatcat:gvv64lcumbabbcnv7646yea5fe

PointGMM: A Neural GMM Network for Point Clouds

Amir Hertz, Rana Hanocka, Raja Giryes, Daniel Cohen-Or
2020 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)  
We also present a novel framework for rigid registration using PointGMM, that learns to disentangle orientation from structure of an input shape.  ...  We present PointGMM, a neural network that learns to generate hGMMs which are characteristic of the shape class, and also coincide with the input point cloud.  ...  Acknowledgement This work is partially supported by the NSF-BSF grant (No. 2017729) and the European research council (ERC-StG 757497 PI Giryes).  ... 
doi:10.1109/cvpr42600.2020.01207 dblp:conf/cvpr/HertzHGC20 fatcat:jdkiljgssrb5dbkxktyu5hcjie

Novel polyp detection technology for colonoscopy: 3D optical scanner

Hakki Refai, Badia Koudsi, Omar Yusef Kudsi
2020 Endoscopy International Open  
Conclusion We demonstrated that a novel 3 D optical scanning system improves the performance of colonoscopy procedures by using a combination of 3 D and 2 D optical scanning and fast, accurate software  ...  After calibration, the system was evaluated in an ex-vivo porcine colon model, using silicon-made polyps. Results The average distance between two adjacent points in the 3 D point cloud was 94 µm.  ...  Refai and Koudsi are CTO and CEO, respectively, of Optecks, LLC. Dr. Kudsi has received teaching course and/or consultancy fees from Intuitive Surgical, Bard-Davol, and W.L.  ... 
doi:10.1055/a-1261-3349 pmid:33140010 pmcid:PMC7577784 fatcat:5ipdtljacbevpcnlwetj4d3uny

A novel point cloud registration using 2D image features

Chien-Chou Lin, Yen-Chou Tai, Jhong-Jin Lee, Yong-Sheng Chen
2017 EURASIP Journal on Advances in Signal Processing  
The proposed method transforms the point clouds into 2D bearing angle images and then uses the 2D feature based matching method, SURF, to find matching pixel pairs between two images.  ...  Since a 3D scanner only captures a scene of a 3D object at a time, a 3D registration for multi-scene is the key issue of 3D modeling.  ...  Acknowledgement This work was supported in part by the Ministry of Science and Technology of Taiwan under the grants no. MOST 104-2221-E-224-038.  ... 
doi:10.1186/s13634-016-0435-y fatcat:cvrgqx6uh5gnpf7pkt52wiaoae

PointGMM: a Neural GMM Network for Point Clouds [article]

Amir Hertz, Rana Hanocka, Raja Giryes, Daniel Cohen-Or
2020 arXiv   pre-print
We also present a novel framework for rigid registration using PointGMM, that learns to disentangle orientation from structure of an input shape.  ...  We present PointGMM, a neural network that learns to generate hGMMs which are characteristic of the shape class, and also coincide with the input point cloud.  ...  Acknowledgement This work is partially supported by the NSF-BSF grant (No. 2017729) and the European research council (ERC-StG 757497 PI Giryes).  ... 
arXiv:2003.13326v1 fatcat:kv5e5jrf6rbvhlbhepghdlov7u

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  ...  Furthermore, we utilize two additional tasks (reconstruction and normal estimation) to enhance the transformation awareness of the proposed DVDs.  ...  Given a source point cloud and a target point cloud, which is rigidly transformed from the source point cloud, we use these two co-occurring inputs to train a feature extraction network that learns global  ... 
arXiv:2201.10034v1 fatcat:s5oy23qh5jhj3bzhefn7gl3y7i

A Graph-Matching Approach for Cross-view Registration of Over-view 2 and Street-view based Point Clouds [article]

Xiao Ling, Rongjun Qin
2022 arXiv   pre-print
video images as the inputs, the proposed method models segments of buildings as nodes of graphs, both detected from the satellite-based and street-view based point clouds, thus to form the registration  ...  well-registered street-view images and point clouds to the satellite point clouds.  ...  Xiaohu Lu's prior assistant to the work.  ... 
arXiv:2202.06857v1 fatcat:so3t6aiq45bkdo2eusisnzaehe

RGB-D mapping: Using Kinect-style depth cameras for dense 3D modeling of indoor environments

Peter Henry, Michael Krainin, Evan Herbst, Xiaofeng Ren, Dieter Fox
2012 The international journal of robotics research  
RGB-D cameras (such as the Microsoft Kinect) are novel sensing systems that capture RGB images along with per-pixel depth information.  ...  We evaluate RGB-D Mapping on two large indoor environments, and show that it effectively combines the visual and shape information available from RGB-D cameras.  ...  Army Research Laboratory under the Collaborative Technology Alliance Program (Cooperative Agreement W911NF-10-2-0016).  ... 
doi:10.1177/0278364911434148 fatcat:m5truaxakredfdqa6u2okotjhu

StickyPillars: Robust and Efficient Feature Matching on Point Clouds using Graph Neural Networks [article]

Kai Fischer, Martin Simon, Florian Oelsner, Stefan Milz, Horst-Michael Gross, Patrick Maeder
2021 arXiv   pre-print
It uses graph neural networks and performs context aggregation on sparse 3D key-points with the aid of transformer based multi-head self and cross-attention.  ...  Modern deep learning based registration approaches present much better results, but suffer from a heavy run-time.  ...  Acknowledgements We would like to thank Valeo, especially Driving Assistance Research Kronach, Germany, and Spleenlab, to make this work possible.  ... 
arXiv:2002.03983v3 fatcat:ftb2qjtnqvhahdlyquu46dfcpi

Deep learning based point cloud registration: an overview

Zhiyuan Zhang, Yuchao Dai, Jiadai Sun
2020 Virtual Reality & Intelligent Hardware  
Point cloud registration aims to find a rigid transformation for aligning one point cloud to another.  ...  Various types of deep learning based point cloud registration methods have been proposed to exploit different aspects of the problem.  ...  Meanwhile, PointNet++ [24] is a key technique used to extract local information in a point cloud.  ... 
doi:10.1016/j.vrih.2020.05.002 fatcat:fvitwguoxje35h356whntjx3ce
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