Feature-enhanced surfaces from incomplete point cloud with segmentation and curve skeleton information
Authors: Wang, M., Fan, Y., Guo, S., Liao, M., Chang, J. and He, D.
Journal: Proceedings - 2017 International Conference on Virtual Reality and Visualization, ICVRV 2017
Pages: 97-102
ISBN: 9781538626368
DOI: 10.1109/ICVRV.2017.00027
Abstract:Raw data of point cloud is often noisy and with topological defects (such as holes), which cause problems including faulty connection and inaccurate structure. As a result, the surface reconstruction of point cloud data is a highly challenging problem. This work proposes a novel method, which improves the surface quality compared with existing methods. Our method combines both the local detailed features and the global topological information during the reconstruction process. To facilitate the feature refinement, we first pre-process the point cloud data by relocating each point, upsampling the point data, and optimizing normals to enhance the features and geometric details. We then identify the topological information by segmenting the geometry and constructing curve skeletons for each part and guide the surface reconstruction with the skeletons by minimal user interaction. We demonstrate the effectiveness of our methods with various examples, where our reconstruction can fill out missing data and preserve sharp features.
https://eprints.bournemouth.ac.uk/32429/
Source: Scopus
Feature-enhanced Surfaces from Incomplete Point Cloud with Segmentation and Curve Skeleton Information
Authors: Wang, M., Fan, Y., Guo, S., Liao, M., Chang, J. and He, D.
Journal: 2017 INTERNATIONAL CONFERENCE ON VIRTUAL REALITY AND VISUALIZATION (ICVRV 2017)
Pages: 97-102
ISSN: 2375-141X
DOI: 10.1109/ICVRV.2017.00027
https://eprints.bournemouth.ac.uk/32429/
Source: Web of Science (Lite)
Feature-enhanced Surfaces from Incomplete Point Cloud with Segmentation and Curve Skeleton Information.
Authors: Wang, M., Fan, Y., Guo, S., Liao, M., Chang, J. and He, D.
Conference: 2017 International Conference on Virtual Reality and Visualization (ICVRV)
Pages: 97-102
Publisher: IEEE
ISBN: 9781538626368
Abstract:Raw data of point cloud is often noisy and with topological defects (such as holes), which cause problems including faulty connection and inaccurate structure. As a result, the surface reconstruction of point cloud data is a highly challenging problem. This work proposes a novel method, which improves the surface quality compared with existing methods. Our method combines both the local detailed features and the global topological information during the reconstruction process. To facilitate the feature refinement, we first pre-process the point cloud data by relocating each point, upsampling the point data, and optimizing normals to enhance the features and geometric details. We then identify the topological information by segmenting the geometry and constructing curve skeletons for each part and guide the surface reconstruction with the skeletons by minimal user interaction. We demonstrate the effectiveness of our methods with various examples, where our reconstruction can fill out missing data and preserve sharp features.
https://eprints.bournemouth.ac.uk/32429/
Source: BURO EPrints