| 書目名稱 | Towards Optimal Point Cloud Processing for 3D Reconstruction |
| 編輯 | Guoxiang Zhang,YangQuan Chen |
| 視頻video | http://file.papertrans.cn/927/926985/926985.mp4 |
| 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 |
| 叢書名稱 | SpringerBriefs in Electrical and Computer Engineering |
| 圖書封面 |  |
| 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 |
| 關(guān)鍵詞 | Point Cloud Processing; 3-D Reconstruction; 3-D Mapping; Cave Mapping; Semantic Mapping; Image Processing |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-3-030-96110-7 |
| isbn_softcover | 978-3-030-96109-1 |
| isbn_ebook | 978-3-030-96110-7Series ISSN 2191-8112 Series E-ISSN 2191-8120 |
| issn_series | 2191-8112 |
| copyright | The Author(s), under exclusive license to Springer Nature Switzerland AG 2022 |
|Archiver|手機(jī)版|小黑屋|
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