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Multiview Point Cloud Filtering for Spatiotemporal Consistency
Citation key 1438Skupin2014
Author Robert Skupin and Thilo Borgmann and Thomas Sikora
Title of Book International Conference on Computer Vision Theory and Applications (VISAPP)
Pages 531–538
Year 2014
DOI 10.5220/0004681805310538
Publisher SCITEPRESS Digital Library
Organization INSTICC
Abstract This work presents algorithms to resample and filter point cloud data reconstructed from multiple cameras and multiple time instants. In an initial resampling stage, a voxel or a surface mesh based approach resamples the point cloud data into a common sampling grid. Subsequently, the resampled data undergoes a filtering stage based on clustering to remove artifacts and achieve spatiotemporal consistency across cameras and time instants. The presented algorithms are evaluated in a view synthesis scenario. Results show that view synthesis with enhanced depth maps as produced by the algorithms leads to less artifacts than synthesis with the original source data.
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