Generalized-CVO: Fast and Correspondence-Free Local Point Cloud Registration with Second Order Riemannian Optimization | Paper Citation Record

Observation 0dfae6cc-ac21-4bec-b5d4-0b04b2767048 · outbound

This paper cites Princeton Univer- sity Press, 2008.

Generalized-CVO: Fast and Correspondence-Free Local Point Cloud Registration with Second Order Riemannian Optimization Princeton Univer- sity Press, 2008

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This paper cites Convergence of itera- tively re-weighted least squares to robust M-estimators.

Generalized-CVO: Fast and Correspondence-Free Local Point Cloud Registration with Second Order Riemannian Optimization Convergence of itera- tively re-weighted least squares to robust M-estimators

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This paper cites Balo: A novel point-to-plane balanced lidar odometry.

Generalized-CVO: Fast and Correspondence-Free Local Point Cloud Registration with Second Order Riemannian Optimization Balo: A novel point-to-plane balanced lidar odometry

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This paper cites Efficient surfel-based SLAM using 3D laser range data in urban environments.

Generalized-CVO: Fast and Correspondence-Free Local Point Cloud Registration with Second Order Riemannian Optimization Efficient surfel-based SLAM using 3D laser range data in urban environments

Reference 4

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This paper cites Method for registration of 3D shapes.

Generalized-CVO: Fast and Correspondence-Free Local Point Cloud Registration with Second Order Riemannian Optimization Method for registration of 3D shapes

Reference 5

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This paper cites Efficient and robust registration on the 3D special Euclidean group.

Generalized-CVO: Fast and Correspondence-Free Local Point Cloud Registration with Second Order Riemannian Optimization Efficient and robust registration on the 3D special Euclidean group

Reference 6

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This paper cites Springer, 2006.

Generalized-CVO: Fast and Correspondence-Free Local Point Cloud Registration with Second Order Riemannian Optimization Springer, 2006

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This paper cites Cambridge University Press, 2023.

Generalized-CVO: Fast and Correspondence-Free Local Point Cloud Registration with Second Order Riemannian Optimization Cambridge University Press, 2023

Reference 8

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Observation 2410cc96-b09f-4d0c-8ec7-ff139d7a202f · outbound

This paper cites On-manifold probabilistic iterative closest point: Application to underwa- ter karst exploration.Int.

Generalized-CVO: Fast and Correspondence-Free Local Point Cloud Registration with Second Order Riemannian Optimization On-manifold probabilistic iterative closest point: Application to underwa- ter karst exploration.Int

Reference 9

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Observation c2633671-3b3e-46fe-8cb0-9cf6826aa38e · outbound

This paper cites Past, present, and future of simultaneous localiza- tion and mapping: Towards the robust-perception age.IEEE Transactions on robotics, 32(6):1309–1332, 2016.

Generalized-CVO: Fast and Correspondence-Free Local Point Cloud Registration with Second Order Riemannian Optimization Past, present, and future of simultaneous localiza- tion and mapping: Towards the robust-perception age.IEEE Transactions on robotics, 32(6):1309–1332, 2016

Reference 10

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Observation 8ca7ffdd-81c1-4e7b-9a6a-e71b96cc8ac8 · outbound

This paper cites ikd-Tree: An Incremental K-D Tree for Robotic Applications.

Generalized-CVO: Fast and Correspondence-Free Local Point Cloud Registration with Second Order Riemannian Optimization ikd-Tree: An Incremental K-D Tree for Robotic Applications

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Observation 930816d1-729c-4a14-b765-b402f1e466d0 · outbound

This paper cites An ICP variant using a point-to-line metric.

Generalized-CVO: Fast and Correspondence-Free Local Point Cloud Registration with Second Order Riemannian Optimization An ICP variant using a point-to-line metric

Reference 12

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Observation ec4dd287-a1ed-44c3-850b-2ba03d35cae3 · outbound

This paper cites Object modelling by regis- tration of multiple range images.Image and vision comput- ing, 10(3):145–155, 1992.

Generalized-CVO: Fast and Correspondence-Free Local Point Cloud Registration with Second Order Riemannian Optimization Object modelling by regis- tration of multiple range images.Image and vision comput- ing, 10(3):145–155, 1992

Reference 13

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Observation 2b45d176-b316-48ee-85a2-73fb5e4db594 · outbound

This paper cites Sc2-pcr: A second order spatial compatibility for efficient and robust point cloud registration.

Generalized-CVO: Fast and Correspondence-Free Local Point Cloud Registration with Second Order Riemannian Optimization Sc2-pcr: A second order spatial compatibility for efficient and robust point cloud registration

Reference 14

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Observation ab5dfd7b-b53c-4ffb-b16e-5952f35a7f88 · outbound

This paper cites Fully convolutional geometric features.

Generalized-CVO: Fast and Correspondence-Free Local Point Cloud Registration with Second Order Riemannian Optimization Fully convolutional geometric features

Reference 15

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Observation 7365dc36-995c-47f6-984e-2d116b66c6a5 · outbound

This paper cites Non- parametric continuous sensor registration.Journal of Ma- chine Learning Research, 22(271):1–50, 2021.

Generalized-CVO: Fast and Correspondence-Free Local Point Cloud Registration with Second Order Riemannian Optimization Non- parametric continuous sensor registration.Journal of Ma- chine Learning Research, 22(271):1–50, 2021

Reference 16

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This paper cites Scan registration using segmented region growing NDT.Int.

Generalized-CVO: Fast and Correspondence-Free Local Point Cloud Registration with Second Order Riemannian Optimization Scan registration using segmented region growing NDT.Int

Reference 17

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Observation 409679bf-46c5-417c-8df6-16d5dfbeedbf · outbound

This paper cites IMLS-SLAM: scan-to-model matching based on 3D data.

Generalized-CVO: Fast and Correspondence-Free Local Point Cloud Registration with Second Order Riemannian Optimization IMLS-SLAM: scan-to-model matching based on 3D data

Reference 18

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Observation b3afab42-a26a-4024-bdaa-8fb478deaebd · outbound

This paper cites One model to drift them all: Physics-informed conditional diffusion model for driving at the limits.

Generalized-CVO: Fast and Correspondence-Free Local Point Cloud Registration with Second Order Riemannian Optimization One model to drift them all: Physics-informed conditional diffusion model for driving at the limits

Reference 19

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Observation 49e062b1-a214-46c8-857e-45193d9f7fa3 · outbound

This paper cites HGMR: Hi- erarchical Gaussian mixtures for adaptive 3D registration.

Generalized-CVO: Fast and Correspondence-Free Local Point Cloud Registration with Second Order Riemannian Optimization HGMR: Hi- erarchical Gaussian mixtures for adaptive 3D registration

Reference 20

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Observation 561d4cfc-71f1-4561-b2db-af6cd3517196 · outbound

This paper cites Springer, 2020.

Generalized-CVO: Fast and Correspondence-Free Local Point Cloud Registration with Second Order Riemannian Optimization Springer, 2020

Reference 21

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Observation 31f3ab4c-3b70-433f-8076-3cc31de6dfd4 · outbound

This paper cites Are we ready for autonomous driving? the KITTI vision benchmark suite.

Generalized-CVO: Fast and Correspondence-Free Local Point Cloud Registration with Second Order Riemannian Optimization Are we ready for autonomous driving? the KITTI vision benchmark suite

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Observation 1195557c-d06e-4141-8a78-dc2bfeff78d7 · outbound

This paper cites Continuous direct sparse visual odometry from RGB-D images.Robotics: Science and Sys- tems, 2019.

Generalized-CVO: Fast and Correspondence-Free Local Point Cloud Registration with Second Order Riemannian Optimization Continuous direct sparse visual odometry from RGB-D images.Robotics: Science and Sys- tems, 2019

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Observation a88c9387-47d5-4765-82cb-e4997c496a1b · outbound

This paper cites Approximate Gauss-Newton methods for nonlinear least squares problems.SIAM Journal on Optimization, 18(1): 106–132, 2007.

Generalized-CVO: Fast and Correspondence-Free Local Point Cloud Registration with Second Order Riemannian Optimization Approximate Gauss-Newton methods for nonlinear least squares problems.SIAM Journal on Optimization, 18(1): 106–132, 2007

Reference 24

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Observation ad25ab2f-e9e3-4601-bf0c-00e0dda36e27 · outbound

This paper cites Approximate KD tree search for efficient ICP.

Generalized-CVO: Fast and Correspondence-Free Local Point Cloud Registration with Second Order Riemannian Optimization Approximate KD tree search for efficient ICP

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Observation 2e75c6c0-61b9-4b5b-8282-c4af8ed60fb5 · outbound

This paper cites Hierarchical optimization on manifolds for online 2d and 3d mapping.

Generalized-CVO: Fast and Correspondence-Free Local Point Cloud Registration with Second Order Riemannian Optimization Hierarchical optimization on manifolds for online 2d and 3d mapping

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This paper cites evo: Python package for the evaluation of odometry and SLAM.https : / / github.

Generalized-CVO: Fast and Correspondence-Free Local Point Cloud Registration with Second Order Riemannian Optimization evo: Python package for the evaluation of odometry and SLAM.https : / / github

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Observation 8b8852f9-fbbb-49f2-b46c-be4e235aab48 · outbound

This paper cites Predator: Registration of 3d point clouds with low overlap.

Generalized-CVO: Fast and Correspondence-Free Local Point Cloud Registration with Second Order Riemannian Optimization Predator: Registration of 3d point clouds with low overlap

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This paper cites Robust estimation of a location parameter.

Generalized-CVO: Fast and Correspondence-Free Local Point Cloud Registration with Second Order Riemannian Optimization Robust estimation of a location parameter

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This paper cites Learn- ing forward dynamics model and informed trajectory sam- pler for safe quadruped navigation.

Generalized-CVO: Fast and Correspondence-Free Local Point Cloud Registration with Second Order Riemannian Optimization Learn- ing forward dynamics model and informed trajectory sam- pler for safe quadruped navigation

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Observation 719964d8-8e14-466e-ab25-2a18fe9dfcbe · outbound

This paper cites Globally consistent 3D LiDAR mapping with GPU- accelerated GICP matching cost factors.Robotics and Aut.

Generalized-CVO: Fast and Correspondence-Free Local Point Cloud Registration with Second Order Riemannian Optimization Globally consistent 3D LiDAR mapping with GPU- accelerated GICP matching cost factors.Robotics and Aut

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Observation 0ee70a9b-5a32-4bb2-91b8-69c7d8c423dd · outbound

This paper cites V oxelized GICP for fast and accurate 3D point cloud registration.

Generalized-CVO: Fast and Correspondence-Free Local Point Cloud Registration with Second Order Riemannian Optimization V oxelized GICP for fast and accurate 3D point cloud registration

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This paper cites LiDAR odometry survey: recent advancements and remaining challenges.Intelligent Service Robotics, 17(2): 95–118, 2024.

Generalized-CVO: Fast and Correspondence-Free Local Point Cloud Registration with Second Order Riemannian Optimization LiDAR odometry survey: recent advancements and remaining challenges.Intelligent Service Robotics, 17(2): 95–118, 2024

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This paper cites Risk- averse model predictive control for racing in adverse con- ditions.Int.

Generalized-CVO: Fast and Correspondence-Free Local Point Cloud Registration with Second Order Riemannian Optimization Risk- averse model predictive control for racing in adverse con- ditions.Int

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This paper cites Unsupervised learning of edges.

Generalized-CVO: Fast and Correspondence-Free Local Point Cloud Registration with Second Order Riemannian Optimization Unsupervised learning of edges

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This paper cites Se3et: Se(3)-equivariant transformer for low-overlap point cloud registration.IEEE Robotics and Automation Letters, 2024.

Generalized-CVO: Fast and Correspondence-Free Local Point Cloud Registration with Second Order Riemannian Optimization Se3et: Se(3)-equivariant transformer for low-overlap point cloud registration.IEEE Robotics and Automation Letters, 2024

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This paper cites PhD thesis, ¨Orebro university, 2009.

Generalized-CVO: Fast and Correspondence-Free Local Point Cloud Registration with Second Order Riemannian Optimization PhD thesis, ¨Orebro university, 2009

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This paper cites The pose estimation of mobile robot based on improved point cloud registration.Int.

Generalized-CVO: Fast and Correspondence-Free Local Point Cloud Registration with Second Order Riemannian Optimization The pose estimation of mobile robot based on improved point cloud registration.Int

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This paper cites R-LOAM: Improving LiDAR odometry and mapping with point-to-mesh features of a known 3D reference object.

Generalized-CVO: Fast and Correspondence-Free Local Point Cloud Registration with Second Order Riemannian Optimization R-LOAM: Improving LiDAR odometry and mapping with point-to-mesh features of a known 3D reference object

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This paper cites RT3000 Product Page, 2024.

Generalized-CVO: Fast and Correspondence-Free Local Point Cloud Registration with Second Order Riemannian Optimization RT3000 Product Page, 2024

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This paper cites Dgcnn: A convolutional neural network over large-scale labeled graphs.Neural Networks, 108:533– 543, 2018.

Generalized-CVO: Fast and Correspondence-Free Local Point Cloud Registration with Second Order Riemannian Optimization Dgcnn: A convolutional neural network over large-scale labeled graphs.Neural Networks, 108:533– 543, 2018

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Observation ceddcb1c-7e2e-4874-b349-cb1163d3c34e · outbound

This paper cites Geotrans- former: Fast and robust point cloud registration with geo- metric transformer.Trans.

Generalized-CVO: Fast and Correspondence-Free Local Point Cloud Registration with Second Order Riemannian Optimization Geotrans- former: Fast and robust point cloud registration with geo- metric transformer.Trans

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Observation 4365407c-066b-4b52-a5b5-6c33c6c16306 · outbound

This paper cites 3D is here: Point cloud library (PCL).

Generalized-CVO: Fast and Correspondence-Free Local Point Cloud Registration with Second Order Riemannian Optimization 3D is here: Point cloud library (PCL)

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Observation 1af57d06-a77c-424d-ab36-09b7967547e2 · outbound

This paper cites Fast point feature histograms (fpfh) for 3d registration.

Generalized-CVO: Fast and Correspondence-Free Local Point Cloud Registration with Second Order Riemannian Optimization Fast point feature histograms (fpfh) for 3d registration

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Observation 3af355a3-5794-4918-a890-45e9c7f1c7c5 · outbound

This paper cites Bad SLAM: Bundle adjusted direct RGB-D SLAM.

Generalized-CVO: Fast and Correspondence-Free Local Point Cloud Registration with Second Order Riemannian Optimization Bad SLAM: Bundle adjusted direct RGB-D SLAM

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This paper cites Generalized-ICP.

Generalized-CVO: Fast and Correspondence-Free Local Point Cloud Registration with Second Order Riemannian Optimization Generalized-ICP

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Observation 43c6f50d-0535-4c40-82f0-9050de9fb61b · outbound

This paper cites Lego-loam: Lightweight and ground-optimized LiDAR odometry and mapping on variable terrain.

Generalized-CVO: Fast and Correspondence-Free Local Point Cloud Registration with Second Order Riemannian Optimization Lego-loam: Lightweight and ground-optimized LiDAR odometry and mapping on variable terrain

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Observation 383ab35f-f786-4d3e-999f-a6c8f647987d · outbound

This paper cites The calculus of M- estimation.The American Statistician, 56(1):29–38, 2002.

Generalized-CVO: Fast and Correspondence-Free Local Point Cloud Registration with Second Order Riemannian Optimization The calculus of M- estimation.The American Statistician, 56(1):29–38, 2002

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Observation 600ab789-8314-453f-8f4f-ae0cb896ea2b · outbound

This paper cites Scalability in percep- tion for autonomous driving: Waymo open dataset.

Generalized-CVO: Fast and Correspondence-Free Local Point Cloud Registration with Second Order Riemannian Optimization Scalability in percep- tion for autonomous driving: Waymo open dataset

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Observation e0272c79-14c6-43d1-9dcf-b603a4f3d66e · outbound

This paper cites A correlation-based ap- proach to robust point set registration.

Generalized-CVO: Fast and Correspondence-Free Local Point Cloud Registration with Second Order Riemannian Optimization A correlation-based ap- proach to robust point set registration

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Observation 4ccaa1fa-1c2e-4d07-9cb1-e54d48414fd6 · outbound

This paper cites Poisson surface reconstruction for LiDAR odometry and mapping.

Generalized-CVO: Fast and Correspondence-Free Local Point Cloud Registration with Second Order Riemannian Optimization Poisson surface reconstruction for LiDAR odometry and mapping

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Observation 7c62f4f5-7299-4c52-b352-776b42f57bd6 · outbound

This paper cites Kiss-ICP: In defense of point-to-point ICP–simple, accurate, and robust registration if done the right way.Robotics and Automation Letters, 8(2):1029–1036, 2023.

Generalized-CVO: Fast and Correspondence-Free Local Point Cloud Registration with Second Order Riemannian Optimization Kiss-ICP: In defense of point-to-point ICP–simple, accurate, and robust registration if done the right way.Robotics and Automation Letters, 8(2):1029–1036, 2023

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Observation 05b9fc4f-6df6-4ecb-92f8-b6af394e26c5 · outbound

This paper cites F- loam: Fast LiDAR odometry and mapping.

Generalized-CVO: Fast and Correspondence-Free Local Point Cloud Registration with Second Order Riemannian Optimization F- loam: Fast LiDAR odometry and mapping

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This paper cites Gaussian processes for machine learning.

Generalized-CVO: Fast and Correspondence-Free Local Point Cloud Registration with Second Order Riemannian Optimization Gaussian processes for machine learning

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This paper cites 3d shapenets: A deep representation for volumetric shapes.

Generalized-CVO: Fast and Correspondence-Free Local Point Cloud Registration with Second Order Riemannian Optimization 3d shapenets: A deep representation for volumetric shapes

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Observation 09973c44-91be-491d-84e6-1673eac4cff8 · outbound

This paper cites FAST-LIO: A fast, robust LiDAR-inertial odometry package by tightly-coupled iter- ated kalman filter, 2021.

Generalized-CVO: Fast and Correspondence-Free Local Point Cloud Registration with Second Order Riemannian Optimization FAST-LIO: A fast, robust LiDAR-inertial odometry package by tightly-coupled iter- ated kalman filter, 2021

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Observation fc514f65-3a09-4968-bb5c-d8fa9fae6f7a · outbound

This paper cites FAST-LIO2: Fast direct LiDAR-inertial odometry.Transac- tions on Robotics, 38(4):2053–2073, 2022.

Generalized-CVO: Fast and Correspondence-Free Local Point Cloud Registration with Second Order Riemannian Optimization FAST-LIO2: Fast direct LiDAR-inertial odometry.Transac- tions on Robotics, 38(4):2053–2073, 2022

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Observation 809ad844-1865-426f-adf2-b8af2b1e46cc · outbound

This paper cites Teaser: Fast and certifiable point cloud registration.Trans.

Generalized-CVO: Fast and Correspondence-Free Local Point Cloud Registration with Second Order Riemannian Optimization Teaser: Fast and certifiable point cloud registration.Trans

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Observation 8f6b08c5-2227-4357-b2a2-c80080030b9e · outbound

This paper cites Go-ICP: A globally optimal solution to 3D ICP point-set registration.Trans.

Generalized-CVO: Fast and Correspondence-Free Local Point Cloud Registration with Second Order Riemannian Optimization Go-ICP: A globally optimal solution to 3D ICP point-set registration.Trans

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Observation e470ef9c-563c-4622-8de5-8151f07fe148 · outbound

This paper cites Mac: Maxi- mal cliques for 3d registration.IEEE Transactions on Pattern Analysis and Machine Intelligence, 2024.

Generalized-CVO: Fast and Correspondence-Free Local Point Cloud Registration with Second Order Riemannian Optimization Mac: Maxi- mal cliques for 3d registration.IEEE Transactions on Pattern Analysis and Machine Intelligence, 2024

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Observation c8c83086-0b0b-47c3-add0-cc0257e7e525 · outbound

This paper cites Cofinet: Reliable coarse-to-fine correspondences for robust pointcloud registration.Advances in Neural Infor- mation Processing Systems, 34:23872–23884, 2021.

Generalized-CVO: Fast and Correspondence-Free Local Point Cloud Registration with Second Order Riemannian Optimization Cofinet: Reliable coarse-to-fine correspondences for robust pointcloud registration.Advances in Neural Infor- mation Processing Systems, 34:23872–23884, 2021

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Observation a7b15670-87cf-456b-b0f9-2f2136b59458 · outbound

This paper cites 3dmatch: Learning local geometric descriptors from RGB-D recon- structions.

Generalized-CVO: Fast and Correspondence-Free Local Point Cloud Registration with Second Order Riemannian Optimization 3dmatch: Learning local geometric descriptors from RGB-D recon- structions

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Observation ab527798-f458-4920-a123-965013741a16 · outbound

This paper cites LOAM: LiDAR odometry and mapping in real-time.

Generalized-CVO: Fast and Correspondence-Free Local Point Cloud Registration with Second Order Riemannian Optimization LOAM: LiDAR odometry and mapping in real-time

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Observation 1ae57f78-1c7f-4331-9483-a947c1fc74c1 · outbound

This paper cites A new framework for registration of se- mantic point clouds from stereo and RGB-D cameras.

Generalized-CVO: Fast and Correspondence-Free Local Point Cloud Registration with Second Order Riemannian Optimization A new framework for registration of se- mantic point clouds from stereo and RGB-D cameras

Reference 64

Resolution: unresolved; no resolver link, observed 2026-06-27T16:45:02.451421Z

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Observation 0e17c8f5-251f-400b-8843-792f678dfe9d · outbound

This paper cites Correspondence-free SE(3) point cloud reg- istration in RKHS via unsupervised equivariant learning.

Generalized-CVO: Fast and Correspondence-Free Local Point Cloud Registration with Second Order Riemannian Optimization Correspondence-free SE(3) point cloud reg- istration in RKHS via unsupervised equivariant learning

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Observation 98e1a812-f097-41ed-9177-9f5f5ed5f5cc · outbound

This paper cites RKHS-BA: A robust correspondence-free multi-view bun- dle adjustment framework for semantic point clouds.Trans.

Generalized-CVO: Fast and Correspondence-Free Local Point Cloud Registration with Second Order Riemannian Optimization RKHS-BA: A robust correspondence-free multi-view bun- dle adjustment framework for semantic point clouds.Trans

Reference 66

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Observation f797545b-0b71-4a67-8f17-75ed0f3a335b · outbound

This paper cites LiDAR- based place recognition for autonomous driving: A survey.

Generalized-CVO: Fast and Correspondence-Free Local Point Cloud Registration with Second Order Riemannian Optimization LiDAR- based place recognition for autonomous driving: A survey

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Observation 553018ee-7d6d-48e9-8b93-e2c6eddde4a1 · outbound

This paper cites Progressive correspondence regenerator for robust 3d regis- tration.

Generalized-CVO: Fast and Correspondence-Free Local Point Cloud Registration with Second Order Riemannian Optimization Progressive correspondence regenerator for robust 3d regis- tration

Reference 68

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Observation 562700de-f9dc-48dd-ad9d-c1dcd53a7204 · outbound

This paper cites SubT-MRS Dataset: Pushing SLAM towards all-weather en- vironments.

Generalized-CVO: Fast and Correspondence-Free Local Point Cloud Registration with Second Order Riemannian Optimization SubT-MRS Dataset: Pushing SLAM towards all-weather en- vironments

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Observation c6a6909c-31e6-4eff-8416-c295c21b8146 · outbound

This paper cites Traj-LO: In defense of LiDAR- only odometry using an effective continuous-time trajectory.

Generalized-CVO: Fast and Correspondence-Free Local Point Cloud Registration with Second Order Riemannian Optimization Traj-LO: In defense of LiDAR- only odometry using an effective continuous-time trajectory

Reference 70

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Observation a0905575-ca1f-4fe4-b172-bc142d784688 · outbound

This paper cites Fast global registration.

Generalized-CVO: Fast and Correspondence-Free Local Point Cloud Registration with Second Order Riemannian Optimization Fast global registration

Reference 71

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Observation a126755a-dc82-42af-b5ae-4fdb3a700bab · outbound

This paper cites Correspondence-free point cloud registration with so(3)- equivariant implicit shape representations.

Generalized-CVO: Fast and Correspondence-Free Local Point Cloud Registration with Second Order Riemannian Optimization Correspondence-free point cloud registration with so(3)- equivariant implicit shape representations

Reference 72

Resolution: unresolved; no resolver link, observed 2026-06-27T16:45:02.451421Z

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Observation 2953d6fd-a8ed-4234-8f9d-d5ce29e9957e · outbound

This paper cites ω∧gω +ω ∧gω +v ∧gv +g ∧ ωω+g ∧ v v v∧gω + 2ω∧gv +g ∧ ωv # . (31) Usinga ∧b=−b ∧a, we have v∧gv +g ∧ v v= 0,ω ∧gω +g ∧ ωω= 0,v ∧gω +g ∧ ωv= 0. (32) Hence, Γ∨(ξ∧,gradf(T)) =.

Generalized-CVO: Fast and Correspondence-Free Local Point Cloud Registration with Second Order Riemannian Optimization ω∧gω +ω ∧gω +v ∧gv +g ∧ ωω+g ∧ v v v∧gω + 2ω∧gv +g ∧ ωv # . (31) Usinga ∧b=−b ∧a, we have v∧gv +g ∧ v v= 0,ω ∧gω +g ∧ ωω= 0,v ∧gω +g ∧ ωv= 0. (32) Hence, Γ∨(ξ∧,gradf(T)) =

Reference 73

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