Depth Images Filtering In Distributed Streaming

1. W. Chau-Chang, C. Min-Shine: Nonmetric Camera Calibration for Underwater Laser Scanning System. IEEE Journal of Oceanic Engineering, vol. 05, 32(2), (2007), 383-399.Search in Google Scholar

2. S. Ferrari, I Frosio, V. Piuri, N.A Borghese: Enhanced vector quantization for data reduction and filtering. Proceedings of 2nd International Symposium on 3D Data Processing, Visualization and Transmission, 3DPVT, (2004), 470–477.Search in Google Scholar

3. S. Gernhardt, X. Cong, M. Eineder, S. Hinz, R. Bamler: Geometrical fusion of multitrack ps point clouds, IEEE Geoscience and Remote Sensing Letters, vol. 9(1), (2012), 38–42.Search in Google Scholar

4. H. Haggag, M. Hossny, D. Filippidis, D. Creighton, S. Nahavandi, V. Puri: Measuring depth accuracy in rgbd cameras. 7th International Conference on Signal Processing and Communication Systems (ICSPCS), (2013), 1–7.10.1109/ICSPCS.2013.6723971Search in Google Scholar

5. L. Hong Xie, Z. Zhao: A new method of cylinder reconstruction based on unorganized point cloud, 18th International Conference on Geoinformatics, (2010), 1–5.Search in Google Scholar

6. P. Kiljański, Optimization of PCD consolidation process in distributed system, Master Thesis, Gdansk University of Technology, 2014Search in Google Scholar

7. P. Li, H. Wang, Z. Liu: A morphological LIDAR point cloud filtering method based on fake scan lines, International Conference on Electronics, Communications and Control (ICECC), (2011), 1228–1231.Search in Google Scholar

8. D. McLeod, J. Jacobson, M. Hardy, C. Embry: Autonomous inspection using an underwater 3D LiDAR. 2013 OCEANS, San Diego, (2013), 1-8.Search in Google Scholar

9. S. Orts-Escolano, V. Morell, J. Garcia-Rodriguez, M. Cazorla: Point cloud data filtering and downsampling using growing neural gas. International Joint Conference on Neural Networks(IJCNN), (2013), 1–8.10.1109/IJCNN.2013.6706719Search in Google Scholar

10. R. Rusu, S. Cousins: 3D is here: Point cloud library (PCL). Proc. of International Conference in Robotics and Automation (ICRA), (2011), 1-4.10.1109/ICRA.2011.5980567Search in Google Scholar

11. K. Santilli, K. Bemis, D. Silver, J. Dastur, P. Rona: Generating realistic images from hydrothermal plume data. Visualization, 2004. IEEE, (2004), 91-98Search in Google Scholar

12. P. Thumbunpeng, M. Ruchanurucks, A Khongm: Surface area calculation using Kinect’s filtered point cloud with an application of burn care. International Conference on Robotics and Biomimetics (ROBIO), (2013), 2166–2169.10.1109/ROBIO.2013.6739790Search in Google Scholar

13. Y. Wan, Z. Miao, Z. Tang: Reconstruction of dense point cloud from uncalibrated widebaseline images. IEEE International Conference on Acoustics Speech and Signal Processing (ICASSP), (2010), 1230–1233.10.1109/ICASSP.2010.5495399Search in Google Scholar

14. Y. Wang, X. Xiang Zhu, R. Bamler, S. Gernhardt: Towards terrasarx street view: Creating city point cloud from multiaspect data stacks. Proc. of Joint Urban Remote Sensing Event (JURSE), (2013), 198–201.Search in Google Scholar

15. H. Wenming, L. Yuanwang, W. Peizhi, W. Xiaojun: Algorithm for 3d point cloud denoising. 3rd International Conference on Genetic and Evolutionary Computing WGEC ’09, (2009), 574–577Search in Google Scholar