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A Robust Rigid Registration Framework of 3D Indoor Scene Point Clouds Based on RGB-D Information
2021
Remote Sensing
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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]
2018
IFIP Advances in Information and Communication Technology
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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
2020
Remote Sensing
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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
2017
ISPRS International Journal of Geo-Information
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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
2017
IEEE Transactions on Image Processing
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2016 pre-print arXiv:1608.05143v1 fatcat:iguu6oiklbc4hlwggusy3stupiOther Versions
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
2017
International Journal for Numerical Methods in Biomedical Engineering
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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
2020
2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
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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
2020
Endoscopy International Open
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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
2017
EURASIP Journal on Advances in Signal Processing
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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]
2020
arXiv
pre-print
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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]
2022
arXiv
pre-print
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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]
2022
arXiv
pre-print
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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
2012
The international journal of robotics research
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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]
2021
arXiv
pre-print
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2020 pre-print arXiv:2002.03983v2 fatcat:mq5pzurbongcbcx2q6ikhbpogqOther Versions
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
2020
Virtual Reality & Intelligent Hardware
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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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