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Titlebook: Towards Optimal Point Cloud Processing for 3D Reconstruction; Guoxiang Zhang,YangQuan Chen Book 2022 The Author(s), under exclusive licens

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书目名称Towards Optimal Point Cloud Processing for 3D Reconstruction
编辑Guoxiang Zhang,YangQuan Chen
视频video
概述Open-access codes allow the reader to reproduce and reuse the results presented.Provides public datasets for reproducible performance testing.Shows the reader how to optimize 3-D Reconstructions
丛书名称SpringerBriefs in Electrical and Computer Engineering
图书封面Titlebook: Towards Optimal Point Cloud Processing for 3D Reconstruction;  Guoxiang Zhang,YangQuan Chen Book 2022 The Author(s), under exclusive licens
描述.This SpringerBrief presents novel methods of approaching challenging problems in the reconstruction of accurate 3D models and serves as an introduction for further 3D reconstruction methods. It develops a 3D reconstruction system that produces accurate results by cascading multiple novel loop detection, sifting, and optimization methods..The authors offer a fast point cloud registration method that utilizes optimized randomness in random sample consensus for surface loop detection. The text also proposes two methods  for surface-loop sifting. One is supported by a sparse-feature-based optimization graph. This graph is more robust to different scan patterns than earlier methods and can cope with tracking failure and recovery. The other is an offline algorithm that can sift loop detections based on their impact on loop optimization results and which is enabled by a dense map posterior metric for 3D reconstruction and mapping performance evaluation works without any costly ground-truth data...The methods presented in .Towards Optimal Point Cloud Processing for 3D Reconstruction. will be of assistance to researchers developing 3D modelling methods and to workers in the wide variety of
出版日期Book 2022
关键词Point Cloud Processing; 3-D Reconstruction; 3-D Mapping; Cave Mapping; Semantic Mapping; Image Processing
版次1
doihttps://doi.org/10.1007/978-3-030-96110-7
isbn_softcover978-3-030-96109-1
isbn_ebook978-3-030-96110-7Series ISSN 2191-8112 Series E-ISSN 2191-8120
issn_series 2191-8112
copyrightThe Author(s), under exclusive license to Springer Nature Switzerland AG 2022
The information of publication is updating

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