Fractal bubble algorithm for simplification of 3D point cloud data

Author:

Shoaib Muhammad1,Cheong Joono2,Kim Younghwan2,Cho Hyeonjoong3

Affiliation:

1. School of Engineering, Royal Melbourne Institute of Technology University, Victoria, Australia

2. Department of Control and Instrumentation Engineering, Korea University, Rep. of Korea

3. Department of Computer and Information Science, Korea University, Rep. of Korea

Publisher

IOS Press

Subject

Artificial Intelligence,General Engineering,Statistics and Probability

Reference19 articles.

1. Applications of point cloud technology in geomechanical characterization, analysis and predictive modeling;Lyons-Baral;Mining Engineering,2016

2. A global clustering approach to point cloud simplification with a specified data reduction ratio;Song;Computer-Aided Design,2008

3. Efficient biased sampling for approximate clustering and outlier detection in large data sets;Kollios;IEEE Transactions on Knowledge and Data Engineering,2003

4. Coarse-to-ne surface simplification with geometric guarantees;Boissonnat;Computer Graphics Forum,2001

5. A progressive point cloud simplification algorithm with preserved sharp edge data;Song;The International Journal of Advanced Manufacturing Technology,2009

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