Depth images filtering in distributed streaming

• Autorzy: Dziubich T. , Szymański J. , Brzeski A. M. , Cychnerski J. , Korłub W. M.

Identyfikatory

DOI

10.1515/pomr-2016-0025

• Języki publikacji: EN

Abstrakty

EN

In this paper, we propose a distributed system for point cloud processing and transferring them via computer network regarding to effectiveness-related requirements. We discuss the comparison of point cloud filters focusing on their usage for streaming optimization. For the filtering step of the stream pipeline processing we evaluate four filters: Voxel Grid, Radial Outliner Remover, Statistical Outlier Removal and Pass Through. For each of the filters we perform a series of tests for evaluating the impact on the point cloud size and transmitting frequency (analysed for various fps ratio). We present results of the optimization process used for point cloud consolidation in a distributed environment. We describe the processing of the point clouds before and after the transmission. Pre- and post-processing allow the user to send the cloud via network without any delays. The proposed pre-processing compression of the cloud and the post-processing reconstruction of it are focused on assuring that the end-user application obtains the cloud with a given precision.

Słowa kluczowe

EN

point cloud processing; distributed system; parallel processing; depth image filtering

• Wydawca: Gdańsk University of Technology, Faculty of Ocean Engineering & Ship Technology
• Czasopismo: Polish Maritime Research
• Rocznik: 2016
• Tom: nr 2
• Strony: 91--98
• Opis fizyczny: Bibliogr. 15 poz., rys.

Twórcy

autor

Dziubich T.

• Gdańsk University of Technology G. Narutowicza 11/12 street 80-233 Gdańsk Poland,

autor

Szymański J.

• Gdańsk University of Technology G. Narutowicza 11/12 street 80-233 Gdańsk Poland,

autor

Brzeski A. M.

• Gdańsk University of Technology G. Narutowicza 11/12 street 80-233 Gdańsk Poland,

autor

Cychnerski J.

• Gdańsk University of Technology G. Narutowicza 11/12 street 80-233 Gdańsk Poland,

autor

Korłub W. M.

• Gdańsk University of Technology G. Narutowicza 11/12 street 80-233 Gdańsk Poland,

Bibliografia

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• 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.
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• 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.
• 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), 574–577

Uwagi

PL

Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę.