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ITS(8), No. 1, March 2007, pp. 133-143.
IEEE DOI
0703
Road safety using laser scanner.
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Luo, Z.P.[Zhi-Peng],
Li, J.[Jonathan],
Xiao, Z.L.[Zhen-Long],
Mou, Z.G.[Z. Geroge],
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Learning high-level features by fusing multi-view representation of
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Elsevier DOI
1903
Convolutional neural networks, 3D object recognition,
MLS point clouds, Multi-view representation, Two-stage fusion network
BibRef
Yue, R.[Rui],
Xu, H.[Hao],
Wu, J.Q.[Jian-Qing],
Sun, R.J.[Ren-Juan],
Yuan, C.W.[Chang-Wei],
Data Registration with Ground Points for Roadside LiDAR Sensors,
RS(11), No. 11, 2019, pp. xx-yy.
DOI Link
1906
BibRef
Zheng, Y.C.[Yu-Chao],
Li, Y.J.[Yu-Jie],
Yang, S.[Shuo],
Lu, H.M.[Hui-Min],
Global-PBNet: A Novel Point Cloud Registration for Autonomous Driving,
ITS(23), No. 11, November 2022, pp. 22312-22319.
IEEE DOI
2212
Point cloud compression, Robustness, Feature extraction,
Deep learning, Training, Space exploration, Registration,
branch-and-bound
BibRef
Li, L.[Liang],
Yang, M.[Ming],
Point Cloud Registration Based on Direct Deep Features With
Applications in Intelligent Vehicles,
ITS(23), No. 8, August 2022, pp. 13346-13357.
IEEE DOI
2208
Feature extraction, Deep learning, Neural networks,
Intelligent vehicles, Histograms, Task analysis, pose estimation
BibRef
Shi, C.H.[Cheng-Hao],
Chen, X.[Xieyuanli],
Lu, H.M.[Hui-Min],
Deng, W.B.[Wen-Bang],
Xiao, J.H.[Jun-Hao],
Dai, B.[Bin],
RDMNet: Reliable Dense Matching Based Point Cloud Registration for
Autonomous Driving,
ITS(24), No. 10, October 2023, pp. 11372-11383.
IEEE DOI
2310
BibRef
Liu, D.R.[Dong-Rui],
Chen, C.C.[Chuan-Chaun],
Xu, C.Q.[Chang-Qing],
Qiu, R.C.[Robert C.],
Chu, L.[Lei],
Self-Supervised Point Cloud Registration With Deep Versatile
Descriptors for Intelligent Driving,
ITS(24), No. 9, September 2023, pp. 9767-9779.
IEEE DOI
2310
BibRef
Chen, S.[Shaoyu],
Wang, X.G.[Xing-Gang],
Cheng, T.H.[Tian-Heng],
Zhang, W.Q.[Wen-Qiang],
Zhang, Q.[Qian],
Huang, C.[Chang],
Liu, W.Y.[Wen-Yu],
AziNorm: Exploiting the Radial Symmetry of Point Cloud for
Azimuth-Normalized 3D Perception,
CVPR22(6377-6386)
IEEE DOI
2210
Point cloud compression, Training, Azimuth, Semantics,
Robot vision systems, Detectors, 3D from multi-view and sensors,
Navigation and autonomous driving
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Wu, B.[Bingli],
Ma, J.[Jie],
Chen, G.[Gaojie],
An, P.[Pei],
Feature Interactive Representation for Point Cloud Registration,
ICCV21(5510-5519)
IEEE DOI
2203
Point cloud compression, Representation learning,
Feature extraction, Stereo, 3D from multiview and other sensors,
Vision for robotics and autonomous vehicles
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Cao, A.Q.[Anh-Quan],
Puy, G.[Gilles],
Boulch, A.[Alexandre],
Marlet, R.[Renaud],
PCAM: Product of Cross-Attention Matrices for Rigid Registration of
Point Clouds,
ICCV21(13209-13218)
IEEE DOI
2203
Point cloud compression, Knowledge engineering, Filtering,
Computer network reliability, Neural networks,
Vision for robotics and autonomous vehicles
BibRef
Lee, J.H.[Jun-Ha],
Kim, S.[Seungwook],
Cho, M.[Minsu],
Park, J.[Jaesik],
Deep Hough Voting for Robust Global Registration,
ICCV21(15974-15983)
IEEE DOI
2203
Point cloud compression, Tensors, Filtering, Pipelines,
Benchmark testing, Vision for robotics and autonomous vehicles,
Vision applications and systems
BibRef
Jubran, I.[Ibrahim],
Maalouf, A.[Alaa],
Kimmel, R.[Ron],
Feldman, D.[Dan],
Provably Approximated Point Cloud Registration,
ICCV21(13249-13258)
IEEE DOI
2203
Point cloud compression, Iterative closest point algorithm,
Economic indicators, Approximation algorithms, Cost function,
Vision for robotics and autonomous vehicles
BibRef
Lee, S.M.[Sang-Mook],
Im, J.J.[Jeong Joon],
Lee, B.H.[Bo-Hee],
Leonessa, A.[Alexander],
Kurdila, A.[Andrew],
A real-time grid map generation and object classification for
ground-based 3D LIDAR data using image analysis techniques,
ICIP10(2253-2256).
IEEE DOI
1009
For navigation or road map creation.
BibRef
Chapter on Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces continues in
Register 3-D LIDAR Data, Profiles .