Try Mobilus Beta
Search tips
Open Access

3D-3D Self-Calibration of Sensors Using Point Cloud Data

Journal Article
2021-01-0086
ISSN: 2641-9645, e-ISSN: 2641-9645
DOI: https://doi.org/10.4271/2021-01-0086
Published April 06, 2021 by SAE International in United States
3D-3D Self-Calibration of Sensors Using Point Cloud Data
Sector:
Citation: Ravindranath, P., Buyukburc, K., and Hasnain, A., "3D-3D Self-Calibration of Sensors Using Point Cloud Data," SAE Int. J. Adv. & Curr. Prac. in Mobility 3(3):1369-1377, 2021, https://doi.org/10.4271/2021-01-0086.
Language: English

References

  1. Jutzi , B. Self-Calibration for LiDAR-based Mobile Mapping Systems 1 3 2019
  2. Peršić , J. Calibration of Heterogeneous Sensor Systems ii 2018
  3. Hillemann , M. , Weinmann , M. , Mueller , M.S. , and Jutzi , B. Automatic Extrinsic Self-Calibration of Mobile Mapping Systems based on Geometric 3D Features Remote Sens. 11 16 1 29 2019
  4. Nagy , B. , and Benedek , C. On-the-Fly Camera and Lidar Calibration Remote Sens. 12 7 1 22 2020
  5. Geiger , A. , Lenz , P. , and Urtasun , R. Are we Ready for Autonomous Driving? The KITTI Vision Benchmark Suite Proc. IEEE Comput. Soc. Conf. Comput. Vis. Pattern Recognit 3354 3361 2012
  6. Hamzah , R.A. , Hamid , A.M.A. , and Md Salim , S.I. The Solution of Stereo Correspondence Problem using Block Matching Algorithm in Stereo Vision Mobile Robot 2nd Int. Conf. Comput. Res. Dev. ICCRD 2010 733 737 2010
  7. Hirschmüller , H. Stereo Processing by Semiglobal Matching and Mutual Information IEEE Trans. Pattern Anal. Mach. Intell. 30 2 328 341 2008
  8. Shi , S. , Wang , X. , and Li , H. PointRCNN: 3D Object Proposal Generation and Detection from Point Cloud Proc. IEEE Comput. Soc. Conf. Comput. Vis. Pattern Recognit 2019-June 770 779 2019
  9. Shi , S. et al. PV-RCNN: Point-Voxel Feature Set Abstraction for 3D Object Detection 2020 10526 10535
  10. Shi , S. , Wang , Z. , Shi , J. , Wang , X. et al. From Points to Parts: 3D Object Detection from Point Cloud with Part-Aware and Part-Aggregation Network IEEE Trans. Pattern Anal. Mach. Intell. 1 1 2020
  11. Qi , C.R. , Su , H. , Mo , K. , and Guibas , L.J. PointNet: Deep Learning on Point sets for 3D Classification and Segmentation Proc. - 30th IEEE Conf. Comput. Vis. Pattern Recognition, CVPR 2017 2017-Januauary 77 85 2017
  12. Graham , B. , Engelcke , M. , and Van Der Maaten , L. 3D Semantic Segmentation with Submanifold Sparse Convolutional Networks Proc. IEEE Comput. Soc. Conf. Comput. Vis. Pattern Recognit 9224 9232 2018
  13. Retinskiy D. Submanifold Sparse Convolutional Networks 1 10 2019
  14. Li , P. , Chen , X. , and Shen , S. Stereo R-CNN Based 3D Object Detection for Autonomous Driving Proc. IEEE Comput. Soc. Conf. Comput. Vis. Pattern Recognit 2019-June 7636 7644 2019
  15. Girshick , R. Fast R-CNN Proc. IEEE Int. Conf. Comput. Vis., vol. 2015 International Conference on Computer Vision, ICCV 2015 1440 1448 2015
  16. He , K. , Gkioxari , G. , Dollár , P. , and Girshick , R. Mask R-CNN IEEE Trans. Pattern Anal. Mach. Intell. 42 2 386 397 2020
  17. Pusztai , Z. , Eichhardt , I. , and Hajder , L. Accurate Calibration of Multi-Lidar-Multi-Camera Systems Sensors (Switzerland) 18 7 1 22 2018
  18. Scaramuzza , D. , Harati , A. , and Siegwart , R. Extrinsic Self Calibration of a Camera and a 3D Laser Range Finder from Natural Scenes IEEE Int. Conf. Intell. Robot. Syst. 4164 4169 2007
  19. Moghadam , P. , Bosse , M. , and Zlot , R. Line-Based Extrinsic Calibration of Range and Image Sensors Proc. - IEEE Int. Conf. Robot. Autom c 3685 3691 2013

Cited By

Recommended Content

Journal Article Physics-Based Simulation Solutions for Testing Performance of Sensors and Perception Algorithm under Adverse Weather Conditions
Technical Paper Creating 3D Virtual Driving Environments for Simulation-Aided Development of Autonomous Driving and Active Safety
Technical Paper Training of Neural Networks with Automated Labeling of Simulated Sensor Data