Chang, H.D.,
Kim, K.I.,
Poston, T.,
An Accurate 3D Localization of a Camera Using a Guide-Mark,
PRL(16), No. 7, July 1995, pp. 749-757.
BibRef
9507
Patruno, C.,
Marani, R.,
Nitti, M.,
d'Orazio, T.,
Stella, E.,
An Embedded Vision System for Real-Time Autonomous Localization Using
Laser Profilometry,
ITS(16), No. 6, December 2015, pp. 3482-3495.
IEEE DOI
1512
Embedded systems
BibRef
Lehtola, V.V.[Ville V.],
Virtanen, J.P.[Juho-Pekka],
Vaaja, M.T.[Matti T.],
Hyyppä, H.[Hannu],
Nüchter, A.[Andreas],
Localization of a mobile laser scanner via dimensional reduction,
PandRS(121), No. 1, 2016, pp. 48-59.
Elsevier DOI
1609
Localization
BibRef
Porzi, L.[Lorenzo],
Bulò, S.R.[Samuel Rota],
Lanz, O.[Oswald],
Valigi, P.[Paolo],
Ricci, E.[Elisa],
An automatic image-to-DEM alignment approach for annotating mountains
pictures on a smartphone,
MVA(28), No. 1-2, February 2017, pp. 101-115.
Springer DOI
1702
BibRef
Jiang, L.[Ling],
Ling, D.Q.[De-Quan],
Zhao, M.W.[Ming-Wei],
Wang, C.[Chun],
Liang, Q.H.[Qiu-Hua],
Liu, K.[Kai],
Effective Identification of Terrain Positions from Gridded DEM Data
Using Multimodal Classification Integration,
IJGI(7), No. 11, 2018, pp. xx-yy.
DOI Link
1812
BibRef
Zheng, L.[Li],
Li, Y.H.[Yu-Hao],
Sun, M.[Meng],
Ji, Z.[Zheng],
Yu, M.Z.[Man-Zhu],
Shu, Q.B.[Qing-Bo],
Non-Rigid Vehicle-Borne LiDAR-Assisted Aerotriangulation,
RS(11), No. 10, 2019, pp. xx-yy.
DOI Link
1906
BibRef
Yin, H.[Huan],
Wang, Y.[Yue],
Ding, X.Q.[Xia-Qing],
Tang, L.[Li],
Huang, S.D.[Shou-Dong],
Xiong, R.[Rong],
3D LiDAR-Based Global Localization Using Siamese Neural Network,
ITS(21), No. 4, April 2020, pp. 1380-1392.
IEEE DOI
2004
Laser radar, Pose estimation,
Neural networks, Task analysis, Robot sensing systems, Measurement,
global localization
BibRef
Wang, T.[Teng],
Somani, A.K.[Arun K.],
Aerial-DEM geolocalization for GPS-denied UAS navigation,
MVA(31), No. 1, January 2020, pp. Article 3.
Springer DOI
2001
BibRef
Mayalu, A.[Alfred],
Kochersberger, K.[Kevin],
Jenkins, B.[Barry],
Malassenet, F.[François],
Lidar Data Reduction for Unmanned Systems Navigation in Urban Canyon,
RS(12), No. 11, 2020, pp. xx-yy.
DOI Link
2006
BibRef
Yu, S.S.[Shang-Shu],
Wang, C.[Cheng],
Yu, Z.L.[Zeng-Lei],
Li, X.[Xin],
Cheng, M.[Ming],
Zang, Y.[Yu],
Deep regression for LiDAR-based localization in dense urban areas,
PandRS(172), 2021, pp. 240-252.
Elsevier DOI
2101
LiDAR-based localization, Deep regression, Multi-task learning,
Residual connection, Inter-task constraint loss
BibRef
Zang, Y.[Yufu],
Meng, F.C.[Fan-Cong],
Lindenbergh, R.[Roderik],
Truong-Hong, L.[Linh],
Li, B.[Bijun],
Deep Localization of Static Scans in Mobile Mapping Point Clouds,
RS(13), No. 2, 2021, pp. xx-yy.
DOI Link
2101
BibRef
Lin, X.[Xiaohu],
Wang, F.[Fuhong],
Yang, B.[Bisheng],
Zhang, W.[Wanwei],
Autonomous Vehicle Localization with Prior Visual Point Cloud Map
Constraints in GNSS-Challenged Environments,
RS(13), No. 3, 2021, pp. xx-yy.
DOI Link
2102
BibRef
de Paula Veronese, L.,
Auat-Cheein, F.,
Mutz, F.,
Oliveira-Santos, T.,
Guivant, J.E.,
de Aguiar, E.,
Badue, C.,
de Souza, A.F.,
Evaluating the Limits of a LiDAR for an Autonomous Driving
Localization,
ITS(22), No. 3, March 2021, pp. 1449-1458.
IEEE DOI
2103
Roads, Laser radar, Satellites,
Sensor phenomena and characterization, Automobiles,
particle filter
BibRef
Li, W.Y.[Wen-Yi],
Liu, G.[Gang],
Cui, X.W.[Xiao-Wei],
Lu, M.Q.[Ming-Quan],
Feature-Aided RTK/LiDAR/INS Integrated Positioning System with
Parallel Filters in the Ambiguity-Position-Joint Domain for Urban
Environments,
RS(13), No. 10, 2021, pp. xx-yy.
DOI Link
2105
BibRef
Wang, Y.S.[Yu-Sheng],
Lou, Y.D.[Yi-Dong],
Zhang, Y.[Yi],
Song, W.W.[Wei-Wei],
Huang, F.[Fei],
Tu, Z.Y.[Zhi-Yong],
A Robust Framework for Simultaneous Localization and Mapping with
Multiple Non-Repetitive Scanning Lidars,
RS(13), No. 10, 2021, pp. xx-yy.
DOI Link
2105
BibRef
Sugiura, K.[Keisuke],
Matsutani, H.[Hiroki],
An FPGA Acceleration and Optimization Techniques for 2D LiDAR SLAM
Algorithm,
IEICE(E104-D), No. 6, June 2021, pp. 789-800.
WWW Link.
2106
BibRef
Gong, Y.S.[Yan-Song],
Sun, F.C.[Feng-Chi],
Yuan, J.[Jing],
Zhu, W.B.[Wen-Bin],
Sun, Q.X.[Qin-Xuan],
A two-level framework for place recognition with 3D LiDAR based on
spatial relation graph,
PR(120), 2021, pp. 108171.
Elsevier DOI
2109
Place recognition, 3D LiDAR, Spatial relation graph, Two-level framework
BibRef
Zhang, J.J.[Jun-Jie],
Khoshelham, K.[Kourosh],
Khodabandeh, A.[Amir],
Seamless Vehicle Positioning by Lidar-GNSS Integration:
Standalone and Multi-Epoch Scenarios,
RS(13), No. 22, 2021, pp. xx-yy.
DOI Link
2112
BibRef
Javanmardi, E.[Ehsan],
Javanmardi, M.[Mahdi],
Gu, Y.[Yanlei],
Kamijo, S.[Shunsuke],
Pre-Estimating Self-Localization Error of NDT-Based Map-Matching From
Map Only,
ITS(22), No. 12, December 2021, pp. 7652-7666.
IEEE DOI
2112
Autonomous vehicles, Sensors,
Laser radar, Layout, Uncertainty, Gaussian distribution, LiDAR
BibRef
Xu, D.[Dong],
Liu, J.B.[Jing-Bin],
Hyyppä, J.[Juha],
Liang, Y.F.[Yi-Fan],
Tao, W.Y.[Wu-Yong],
A heterogeneous 3D map-based place recognition solution using virtual
LiDAR and a polar grid height coding image descriptor,
PandRS(183), 2022, pp. 1-18.
Elsevier DOI
2201
Place recognition, Heterogeneous 3D map, Point cloud,
Global feature descriptor, Polar grid height coding image
BibRef
Xu, D.[Dong],
Liu, J.B.[Jing-Bin],
Liang, Y.F.[Yi-Fan],
Lv, X.F.[Xuan-Fan],
Hyyppä, J.[Juha],
A LiDAR-based single-shot global localization solution using a
cross-section shape context descriptor,
PandRS(189), 2022, pp. 272-288.
Elsevier DOI
2206
Global localization, HD map, LiDAR, Global feature descriptor, Place recognition
BibRef
Salles, R.N.[Roberto Neves],
de Campos Velho, H.F.[Haroldo Fraga],
Shiguemori, E.H.[Elcio Hideiti],
Automatic Position Estimation Based on Lidar X Lidar Data for
Autonomous Aerial Navigation in the Amazon Forest Region,
RS(14), No. 2, 2022, pp. xx-yy.
DOI Link
2201
BibRef
Hui, L.[Le],
Cheng, M.M.[Ming-Mei],
Xie, J.[Jin],
Yang, J.[Jian],
Cheng, M.M.[Ming-Ming],
Efficient 3D Point Cloud Feature Learning for Large-Scale Place
Recognition,
IP(31), 2022, pp. 1258-1270.
IEEE DOI
2202
Power transformer insulation, Electric vehicle charging,
Transformers, Training, Windings, Optimization, global descriptor
BibRef
Hui, L.[Le],
Yang, H.[Hang],
Cheng, M.M.[Ming-Mei],
Xie, J.[Jin],
Yang, J.[Jian],
Pyramid Point Cloud Transformer for Large-Scale Place Recognition,
ICCV21(6078-6087)
IEEE DOI
2203
Point cloud compression, Deep learning, Codes, Aggregates,
Feature extraction, Transformers, Stereo,
Recognition and classification
BibRef
Shi, C.H.[Chen-Hui],
Li, J.[Jing],
Gong, J.H.[Jian-Hua],
Yang, B.H.[Bang-Hui],
Zhang, G.Y.[Guo-Yong],
An Improved Lightweight Deep Neural Network with Knowledge
Distillation for Local Feature Extraction and Visual Localization
Using Images and LiDAR Point Clouds,
PandRS(184), 2022, pp. 177-188.
Elsevier DOI
2202
Deep local features, Lightweight network,
Knowledge distillation, Visual localization, LiDAR, Extreme lighting conditions
BibRef
Yan, L.[Li],
Hu, X.[Xiao],
Zhao, L.[Leyang],
Chen, Y.[Yu],
Wei, P.C.[Peng-Cheng],
Xie, H.[Hong],
DGS-SLAM: A Fast and Robust RGBD SLAM in Dynamic Environments
Combined by Geometric and Semantic Information,
RS(14), No. 3, 2022, pp. xx-yy.
DOI Link
2202
BibRef
Chen, Z.J.[Zhi-Jian],
Xu, A.G.[Ai-Gong],
Sui, X.[Xin],
Wang, C.Q.[Chang-Qiang],
Wang, S.[Siyu],
Gao, J.X.[Jia-Xin],
Shi, Z.X.[Zheng-Xu],
Improved-UWB/LiDAR-SLAM Tightly Coupled Positioning System with NLOS
Identification Using a LiDAR Point Cloud in GNSS-Denied Environments,
RS(14), No. 6, 2022, pp. xx-yy.
DOI Link
2204
BibRef
Niewola, A.[Adam],
Mobile Robot 6-D Localization Using 3-D Gaussian Mixture Maps in
GPS-Denied Environments,
IEEE_Int_Sys(37), No. 1, January 2022, pp. 79-88.
IEEE DOI
2205
Mobile robots, Robots, Laser radar,
Sensors, Feature extraction, Robot kinematics
BibRef
Lee, S.[Soomok],
Seo, S.W.[Seung-Woo],
Fail-Safe Multi-Modal Localization Framework Using Heterogeneous
Map-Matching Sources,
ITS(23), No. 5, May 2022, pp. 4008-4020.
IEEE DOI
2205
Sensors, Laser radar, Sensor systems, Roads, Cameras,
Sensor phenomena and characterization,
autonomous vehicle
BibRef
Yu, S.S.[Shang-Shu],
Wang, C.[Cheng],
Wen, C.L.[Cheng-Lu],
Cheng, M.[Ming],
Liu, M.H.[Ming-Hao],
Zhang, Z.H.[Zhi-Hong],
Li, X.[Xin],
LiDAR-based localization using universal encoding and memory-aware
regression,
PR(128), 2022, pp. 108685.
Elsevier DOI
2205
BibRef
And:
Corrigendum:
PR(132), 2022, pp. 108915.
Elsevier DOI
2209
LiDAR localization, Absolute pose regression,
Universal encoding, Privacy preserving, Memory-aware regression
BibRef
Dai, D.[Deyun],
Wang, J.[Jikai],
Chen, Z.H.[Zong-Hai],
Bao, P.[Peng],
SC-LPR: Spatiotemporal context based LiDAR place recognition,
PRL(156), 2022, pp. 160-166.
Elsevier DOI
2205
Place recognition, 3D Lidar scans, Spatiotemporal information,
Cosine tensor network
BibRef
Zhao, P.[Pufan],
Li, S.[Song],
Ma, Y.[Yue],
Liu, X.Y.[Xin-Yuan],
Yang, J.[Jian],
Yu, D.[Dian],
A new terrain matching method for estimating laser pointing and
ranging systematic biases for spaceborne photon-counting laser
altimeters,
PandRS(188), 2022, pp. 220-236.
Elsevier DOI
2205
Laser altimeter, Photon-counting, Systematic bias,
Geolocation accuracy, Terrain matching, ICESat-2
BibRef
Yin, H.[Huan],
Chen, R.J.[Run-Jian],
Wang, Y.[Yue],
Xiong, R.[Rong],
RaLL: End-to-End Radar Localization on Lidar Map Using Differentiable
Measurement Model,
ITS(23), No. 7, July 2022, pp. 6737-6750.
IEEE DOI
2207
Radar, Laser radar, Location awareness, Radar tracking,
Simultaneous localization and mapping, Neural networks,
Kalman filter
BibRef
Chou, C.C.[Chih-Chung],
Chou, C.F.[Cheng-Fu],
Efficient and Accurate Tightly-Coupled Visual-Lidar SLAM,
ITS(23), No. 9, September 2022, pp. 14509-14523.
IEEE DOI
2209
Laser radar, Simultaneous localization and mapping,
Visualization, Cameras, Point cloud compression, Bundle adjustment,
vision
BibRef
Xie, Y.T.[Yu-Ting],
Zhang, Y.[Yachen],
Chen, L.[Long],
Cheng, H.[Hui],
Tu, W.[Wei],
Cao, D.[Dongpu],
Li, Q.Q.[Qing-Quan],
RDC-SLAM: A Real-Time Distributed Cooperative SLAM System Based on 3D
LiDAR,
ITS(23), No. 9, September 2022, pp. 14721-14730.
IEEE DOI
2209
Simultaneous localization and mapping, Robots, Robot kinematics,
Laser radar, Task analysis, Real-time systems, 3D LiDAR,
distributed system
BibRef
Chen, Z.J.[Zhi-Jian],
Xu, A.[Aigong],
Sui, X.[Xin],
Hao, Y.T.[Yu-Ting],
Zhang, C.[Cong],
Shi, Z.X.[Zheng-Xu],
NLOS Identification- and Correction-Focused Fusion of UWB and
LiDAR-SLAM Based on Factor Graph Optimization for High-Precision
Positioning with Reduced Drift,
RS(14), No. 17, 2022, pp. xx-yy.
DOI Link
2209
BibRef
Kim, K.[Kyuwon],
Im, J.[Junhyuck],
Jee, G.[Gyuin],
Tunnel Facility Based Vehicle Localization in Highway Tunnel Using 3D
LIDAR,
ITS(23), No. 10, October 2022, pp. 17575-17583.
IEEE DOI
2210
Location awareness, Laser radar, Road transportation,
Point cloud compression, Global Positioning System,
map matching
BibRef
Wang, G.[Gang],
Gao, X.Y.[Xin-Yu],
Zhang, T.Z.[Tong-Zhou],
Xu, Q.[Qian],
Zhou, W.[Wei],
LiDAR Odometry and Mapping Based on Neighborhood Information
Constraints for Rugged Terrain,
RS(14), No. 20, 2022, pp. xx-yy.
DOI Link
2211
BibRef
Kang, M.S.[Min-Su],
Ahn, J.H.[Jae-Hoon],
Im, J.U.[Ji-Ung],
Won, J.H.[Jong-Hoon],
Lidar- and V2X-Based Cooperative Localization Technique for
Autonomous Driving in a GNSS-Denied Environment,
RS(14), No. 22, 2022, pp. xx-yy.
DOI Link
2212
BibRef
Fang, S.[Susu],
Li, H.[Hao],
Yang, M.[Ming],
LiDAR SLAM Based Multivehicle Cooperative Localization Using Iterated
Split CIF,
ITS(23), No. 11, November 2022, pp. 21137-21147.
IEEE DOI
2212
Location awareness, Correlation, Soft sensors, State estimation,
Robustness, Laser radar, Simultaneous localization and mapping,
autonomous vehicle
BibRef
Chen, K.Y.[Kuang-Yi],
Yu, H.[Huai],
Yang, W.[Wen],
Yu, L.[Lei],
Scherer, S.[Sebastian],
Xia, G.S.[Gui-Song],
I2D-Loc: Camera localization via image to LiDAR depth flow,
PandRS(194), 2022, pp. 209-221.
Elsevier DOI
2212
Camera localization, 2D-3D registration, Flow estimation,
Depth completion, Neural network
BibRef
Zhu, H.[Hui],
Kuang, X.[Xinkai],
Su, T.[Tao],
Chen, Z.Y.[Zi-Yu],
Yu, B.[Biao],
Li, B.[Bichun],
Dual-Constraint Registration LiDAR SLAM Based on Grid Maps
Enhancement in Off-Road Environment,
RS(14), No. 22, 2022, pp. xx-yy.
DOI Link
2212
BibRef
Liu, Y.J.[Yan-Jie],
Wang, C.[Chao],
Wu, H.[Heng],
Wei, Y.L.[Yan-Long],
Ren, M.X.[Mei-Xuan],
Zhao, C.S.[Chang-Sen],
Improved LiDAR Localization Method for Mobile Robots Based on
Multi-Sensing,
RS(14), No. 23, 2022, pp. xx-yy.
DOI Link
2212
BibRef
Dawson, E.[Emma],
Rashed, M.A.[Marwan A.],
Abdelfatah, W.[Walid],
Noureldin, A.[Aboelmagd],
Radar-Based Multisensor Fusion for Uninterrupted Reliable Positioning
in GNSS-Denied Environments,
ITS(23), No. 12, December 2022, pp. 23384-23398.
IEEE DOI
2212
Radar, Doppler radar, Global navigation satellite system,
Navigation, Sensors, Radar detection, Inertial sensors, Positioning,
data analysis
BibRef
Tao, Z.X.[Zhong-Xing],
Xue, J.R.[Jian-Ru],
Wang, D.[Di],
Li, G.X.[Geng-Xin],
Fang, J.[Jianwu],
An Adaptive Invariant EKF for Map-Aided Localization Using 3D Point
Cloud,
ITS(23), No. 12, December 2022, pp. 24057-24070.
IEEE DOI
2212
Location awareness, Point cloud compression, Vehicle dynamics,
Customer relationship management, Noise measurement,
Gaussian process regression
BibRef
Park, J.[Joohyun],
Cho, Y.G.[Young-Gun],
Shin, Y.S.[Young-Sik],
Nonparametric Background Model-Based LiDAR SLAM in Highly Dynamic
Urban Environments,
ITS(23), No. 12, December 2022, pp. 24190-24205.
IEEE DOI
2212
Laser radar, Dynamics, Vehicle dynamics,
Simultaneous localization and mapping, Heuristic algorithms,
dynamic objects
BibRef
Li, S.X.[Shuai-Xin],
Tian, B.[Bin],
Zhu, X.Z.[Xiao-Zhou],
Gui, J.J.[Jian-Jun],
Yao, W.[Wen],
Li, G.Y.[Guang-Yun],
InTEn-LOAM: Intensity and Temporal Enhanced LiDAR Odometry and
Mapping,
RS(15), No. 1, 2023, pp. xx-yy.
DOI Link
2301
BibRef
Wu, H.Y.[Hai-Yang],
Wu, W.[Wei],
Qi, X.Y.[Xing-Yu],
Wu, C.H.[Chao-Hong],
An, L.[Lina],
Zhong, R.[Ruofei],
Planar Constraint Assisted LiDAR SLAM Algorithm Based on Manhattan
World Assumption,
RS(15), No. 1, 2023, pp. xx-yy.
DOI Link
2301
BibRef
Yu, S.S.[Shang-Shu],
Wang, C.[Cheng],
Lin, Y.[Yitai],
Wen, C.L.[Cheng-Lu],
Cheng, M.[Ming],
Hu, G.S.[Guo-Sheng],
STCLoc: Deep LiDAR Localization With Spatio-Temporal Constraints,
ITS(24), No. 1, January 2023, pp. 489-500.
IEEE DOI
2301
Location awareness, Point cloud compression, Laser radar,
Task analysis, Robots, Encoding, LiDAR localization,
spatio-temporal constraints
BibRef
Xu, Y.F.[Yi-Fang],
Ding, S.[Sheng],
Chen, P.M.[Pei-Min],
Tang, H.L.[Hai-Long],
Ren, H.K.[Hong-Kai],
Huang, H.B.[Hua-Bing],
Horizontal Geolocation Error Evaluation and Correction on
Full-Waveform LiDAR Footprints via Waveform Matching,
RS(15), No. 3, 2023, pp. xx-yy.
DOI Link
2302
BibRef
Zhong, Y.[Yihan],
Huang, F.[Feng],
Zhang, J.C.[Jia-Chen],
Wen, W.S.[Wei-Song],
Hsu, L.T.[Li-Ta],
Low-cost solid-state LiDAR/inertial-based localization with prior map
for autonomous systems in urban scenarios,
IET-ITS(17), No. 3, 2023, pp. 470-482.
DOI Link
2303
BibRef
Min, Z.X.[Zhi-Xiang],
Khosravan, N.[Naji],
Bessinger, Z.[Zachary],
Narayana, M.[Manjunath],
Kang, S.B.[Sing Bing],
Dunn, E.[Enrique],
Boyadzhiev, I.[Ivaylo],
LASER: LAtent SpacE Rendering for 2D Visual Localization,
CVPR22(11112-11121)
IEEE DOI
2210
Location awareness, Learning systems, Visualization,
Monte Carlo methods, Lasers, Robot vision systems, Pose estimation,
Robot vision
BibRef
Kim, J.[Junho],
Choi, C.[Changwoon],
Jang, H.[Hojun],
Kim, Y.M.[Young Min],
PICCOLO: Point Cloud-Centric Omnidirectional Localization,
ICCV21(3293-3303)
IEEE DOI
2203
Location awareness, Point cloud compression, Training,
Cloud computing, Visualization, Image color analysis,
Vision for robotics and autonomous vehicles
BibRef
Xia, Y.[Yan],
Xu, Y.S.[Yu-Sheng],
Li, S.[Shuang],
Wang, R.[Rui],
Du, J.[Juan],
Cremers, D.[Daniel],
Stilla, U.[Uwe],
SOE-Net: A Self-Attention and Orientation Encoding Network for Point
Cloud based Place Recognition,
CVPR21(11343-11352)
IEEE DOI
2111
Measurement, Codes, Benchmark testing, Encoding, Pattern recognition
BibRef
Komorowski, J.[Jacek],
Improving Point Cloud Based Place Recognition with Ranking-based Loss
and Large Batch Training,
ICPR22(3699-3705)
IEEE DOI
2212
BibRef
Earlier:
MinkLoc3D: Point Cloud Based Large-Scale Place Recognition,
WACV21(1789-1798)
IEEE DOI
2106
Training, Point cloud compression, Protocols,
Image color analysis, point cloud.
Convolutional codes, Location awareness, Learning systems.
BibRef
Sunegård, A.,
Svensson, L.,
Sattler, T.,
Deep LiDAR localization using optical flow sensor-map correspondences,
3DV20(838-847)
IEEE DOI
2102
Location awareness, Laser radar,
Correlation, Transforms, Optical sensors
BibRef
Lee, J.,
Bae, J.,
Choi, Y.,
Park, I.,
Hong, S.,
Sohn, H.,
Point Cloud Transformation Using Sensor Calibration Information for Map
Data Adjustment,
ISPRS20(B3:521-525).
DOI Link
2012
Autonomous vehicle localization, GNSS is not enough. Use Lidar and model.
BibRef
Shi, T.,
Shen, S.,
Gao, X.,
Zhu, L.,
Visual Localization Using Sparse Semantic 3D Map,
ICIP19(315-319)
IEEE DOI
1910
Visual localization, semantic segmentation, image retrieval,
camera pose estimation
BibRef
Wang, P.[Peng],
Yang, R.G.[Rui-Gang],
Cao, B.B.[Bin-Bin],
Xu, W.[Wei],
Lin, Y.Q.[Yuan-Qing],
DeLS-3D: Deep Localization and Segmentation with a 3D Semantic Map,
CVPR18(5860-5869)
IEEE DOI
1812
For driving or augmented reality.
Cameras, Semantics, Image segmentation,
Pose estimation, Streaming media, Sensors
BibRef
Sun, X.,
Xie, Y.,
Luo, P.,
Wang, L.,
A Dataset for Benchmarking Image-Based Localization,
CVPR17(5641-5649)
IEEE DOI
1711
Cameras, Laser radar, Measurement, Solid modeling,
Training, Visualization
BibRef
Xavier, R.S.,
da Silva, B.M.F.,
Gonzalves, L.M.G.,
Accuracy Analysis of Augmented Reality Markers for Visual Mapping and
Localization,
WVC17(73-77)
IEEE DOI
1804
SLAM (robots), augmented reality, cameras, image reconstruction,
pose estimation, robot vision, 3D scene reconstruction,
Visualization
BibRef
Gordon, M.[Marvin],
Hebel, M.[Marcus],
Arens, M.[Michael],
A Descriptor and Voting Scheme for Fast 3D Self-Localization in
Man-Made Environments,
CRV16(319-326)
IEEE DOI
1612
3D descriptors; Hough voting; LIDAR; MLS; geometric validation
BibRef
Sizikova, E.[Elena],
Singh, V.K.[Vivek K.],
Georgescu, B.[Bogdan],
Halber, M.[Maciej],
Ma, K.[Kai],
Chen, T.[Terrence],
Enhancing Place Recognition Using Joint Intensity:
Depth Analysis and Synthetic Data,
VARVAI16(III: 901-908).
Springer DOI
1611
BibRef
Beach, G.[Glenn],
Cohen, C.J.[Charles J.],
Haanpaa, D.[Doug],
Rowe, S.[Steve],
Mahal, P.[Pritpaul],
3D camera identification for enabling robotic manipulation,
AIPR15(1-6)
IEEE DOI
1605
cameras
BibRef
Milford, M.[Michael],
Lowry, S.[Stephanie],
Sunderhauf, N.[Niko],
Shirazi, S.[Sareh],
Pepperell, E.[Edward],
Upcroft, B.[Ben],
Shen, C.H.[Chun-Hua],
Lin, G.S.[Guo-Sheng],
Liu, F.[Fayao],
Cadena, C.[Cesar],
Reid, I.D.[Ian D.],
Sequence searching with deep-learnt depth for condition- and
viewpoint-invariant route-based place recognition,
CVVT15(18-25)
IEEE DOI
1510
Computational modeling
BibRef
Kanai, S.,
Hatakeyama, R.,
Date, H.,
Improvement of 3D Monte Carlo Localization Using a Depth Camera and
Terrestrial Laser Scanner,
Seamless15(61-66).
DOI Link
1508
BibRef
Ventura, J.[Jonathan],
Arth, C.[Clemens],
Reitmayr, G.[Gerhard],
Schmalstieg, D.[Dieter],
A Minimal Solution to the Generalized Pose-and-Scale Problem,
CVPR14(422-429)
IEEE DOI
1409
3d computer vision
BibRef
Hao, Q.A.[Qi-Ang],
Cai, R.[Rui],
Li, Z.W.[Zhi-Wei],
Zhang, L.[Lei],
Pang, Y.W.[Yan-Wei],
Wu, F.[Feng],
3D visual phrases for landmark recognition,
CVPR12(3594-3601).
IEEE DOI
1208
Triangular facet on the surface.
BibRef
Shen, J.L.[Jia-Li],
Miller, P.,
Zhou, H.Y.[Hui-Yu],
Loughlin, M.,
Multi-camera detection association for 3D localisation,
MultiCamera11(480-485).
IEEE DOI
1111
BibRef
Li, Y.P.[Yun-Peng],
Snavely, N.[Noah],
Huttenlocher, D.P.[Dan P.],
Fua, P.[Pascal],
Worldwide Pose Estimation Using 3D Point Clouds,
ECCV12(I: 15-29).
Springer DOI
1210
BibRef
Zhu, Z.W.[Zhi-Wei],
Chiu, H.P.[Han-Pang],
Oskiper, T.[Taragay],
Ali, S.[Saad],
Hadsell, R.[Raia],
Samarasekera, S.[Supun],
Kumar, R.[Rakesh],
High-precision localization using visual landmarks fused with range
data,
CVPR11(81-88).
IEEE DOI
1106
BibRef
Tong, C.H.[Chi Hay],
Barfoot, T.D.[Timothy D.],
A Comparison of the EKF, SPKF, and the Bayes Filter for Landmark-Based
Localization,
CRV10(199-206).
IEEE DOI
1005
BibRef
Li, Y.P.[Yun-Peng],
Snavely, N.[Noah],
Huttenlocher, D.P.[Daniel P.],
Location Recognition Using Prioritized Feature Matching,
ECCV10(II: 791-804).
Springer DOI
1009
BibRef
Yousif, H.[Hamad],
Li, J.[Jonathan],
Chapman, M.[Mike],
Enhancement of positioning accuracy of terrestrial LiDAR mobile mapping
systems,
CGC10(48).
PDF File.
1006
BibRef
Yousif, H.[Hamad],
Li, J.[Jonathan],
Shu, Y.,
Chapman, M.[Mike],
Accuracy Enhancement Of Terrestrial Mobile Lidar Data Using Theory Of
Assimilation,
CloseRange10(xx-yy).
PDF File.
1006
BibRef
Brenner, C.[Claus],
Vehicle Localization using Landmarks obtained by a Lidar Mobile Mapping
System,
PCVIA10(A:139).
PDF File.
1009
BibRef
Earlier:
Global Localization of Vehicles Using Local Pole Patterns,
DAGM09(61-70).
Springer DOI
0909
First a full 3D model from scanner, extract features, then localize
based on these features.
BibRef
Brenner, C.,
Elias, B.,
Extracting Landmarks for Car Navigation Systems using Existing GIS
Databases and Laser Scanning,
PIA05(xx-yy).
PDF File.
0509
BibRef
Moras, J.,
Cherfaoui, V.,
Bonnifait, P.,
A lidar perception scheme for intelligent vehicle navigation,
ICARCV10(1809-1814).
IEEE DOI
1109
BibRef
Zhu, Z.W.[Zhi-Wei],
Oskiper, T.[Taragay],
Samarasekera, S.[Supun],
Kumar, R.[Rakesh],
Sawhney, H.S.[Harpreet S.],
Real-time global localization with a pre-built visual landmark database,
CVPR08(1-8).
IEEE DOI
0806
BibRef
Chin, T.J.[Tat-Jun],
Goh, H.L.[Han-Lin],
Lim, J.H.[Joo-Hwee],
Boosting descriptors condensed from video sequences for place
recognition,
VisLoc08(1-8).
IEEE DOI
0806
BibRef
Khoury, R.,
An Enhanced Positioning Algorithm for a Self-Referencing Hand-Held 3D
Sensor,
CRV06(44-44).
IEEE DOI
0607
Match triangles of features.
BibRef
Bakambu, J.N.,
Allard, P.,
Dupuis, E.,
3D Terrain Modeling for Rover Localization and Navigation,
CRV06(61-61).
IEEE DOI
0607
BibRef
Lisitsyn, V.M.[Vjacheslav M.],
Danovsky, V.N.[Vladislav N.],
Tikhonova, S.V.[Svetlana V.],
Method of Vehicle Navigation System Correction Based on Processing of
Distance Images Obtained by Laser Locator,
PCV02(B: 157).
0305
BibRef
Wolf, J.[Jürgen],
Burgard, W.[Wolfram],
Burkhardt, H.[Hans],
Using an Image Retrieval System for Vision-Based Mobile Robot
Localization,
CIVR02(108-119).
Springer DOI
0208
BibRef
Dellaert, F.[Frank],
Burgard, W.[Wolfram],
Fox, D.[Dieter],
Thrun, S.[Sebastian],
Using the Condensation Algorithm for Robust, Vision-based Mobile Robot
Localization,
CVPR99(II: 588-594).
IEEE DOI Locate where you are and generate map.
BibRef
9900
Haehnel, D.[Dirk],
Burgard, W.[Wolfram],
Fox, D.[Dieter],
Thrun, S.[Sebastian],
An efficient FastSLAM algorithm for generating
maps of large-scale cyclic environments from raw laser range measurements,
IROS03(xx-yy).
BibRef
0300
Burgard, W.[Wolfram],
Fox, D.[Dieter],
Thrun, S.[Sebastian],
Active Mobile Robot Localization,
IJCAI97(1346-1352).
BibRef
9700
Thrun, S.[Sebastian],
Burgard, W.[Wolfram],
Fox, D.[Dieter],
A Probabilistic Approach for Concurrent Map Acquisition and
Localization for Mobile Robots,
CMU-CS-TR--97-183, October 1997.
HTML Version.
BibRef
9710
Thrun, S.[Sebastian],
A Bayesian Approach to Landmark Discovery and Active Perception
in Mobile Robot Navigation,
CMU-CS-TR-96-122, May 1996.
PS File.
BibRef
9605
Chapter on Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following continues in
Localization, Georeference, Urban Regions, City Models, Building Models .