Simplification method of 3D point cloud data for ray trace simulation in indoor environment
Author:
Affiliation:
1. Kozo Keikaku Engineering Inc.
2. Tokyo Institute of Technology
Publisher
Institute of Electronics, Information and Communications Engineers (IEICE)
Subject
General Medicine
Link
https://www.jstage.jst.go.jp/article/comex/9/6/9_2019SPL0010/_pdf
Reference5 articles.
1. [1] Z. Chen, K. Saito, W. Okamura, Y. Kishiki, and J. Takada, “3D point cloud data simplification method for electromagnetic simulation in indoor environment,” IEICE Technical Report, SRW2018-49, pp. 19–24, Jan. 2019.
2. [2] R. B. Rusu and S. Cousins, “3D is here: Point Cloud Library (PCL),” 2011 IEEE International Conference on Robotics and Automation, Shanghai, pp. 1–4, 2011. DOI:10.1109/ICRA.2011.5980567
3. [3] M. A. Fischler and R. C. Bolles, “Random sample consensus: A paradigm for model fitting with applications to image analysis and automated cartography,” Commun. ACM, vol. 24, no. 6, pp. 381–395, 1981. DOI:10.1145/358669.358692
4. [4] K. Saito, J.-I. Takada, and M. Kim, “Dense multipath component characteristics in 11-GHz-band indoor environments,” IEEE Trans. Antennas Propag., vol. 65, no. 9, pp. 4780–4789, Sept. 2017. DOI:10.1109/TAP.2017.2728087
5. [5] E. Costa, “Ray tracing based on the method of images for propagation simulation in cellular environments,” Tenth International Conference on Antennas and Propagation, Edinburgh, vol. 2, pp. 204–209, 1997. DOI:10.1049/cp:19970364
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