Vui lòng dùng định danh này để trích dẫn hoặc liên kết đến tài liệu này: http://thuvienso.vanlanguni.edu.vn/handle/Vanlang_TV/33517
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dc.contributor.authorRodríguez-Gonzálvez, Pablo-
dc.contributor.authorNocerino, Erica-
dc.contributor.authorToschi, Isabella-
dc.contributor.authorChiang (Eds.), Kai-Wei-
dc.date.accessioned2021-08-16T10:22:27Z-
dc.date.available2021-08-16T10:22:27Z-
dc.date.issued2019-
dc.identifier.issn978-3-03928-018-6-
dc.identifier.urihttp://thuvienso.vanlanguni.edu.vn/handle/Vanlang_TV/33517-
dc.descriptionvii, 322 p. ; 177 Mb ; https://doi.org/10.3390/books978-3-03928-019-3 ; CC BY-NC-NDvi
dc.description.abstract"Mobile Mapping technologies have seen a rapid growth of research activity and interest in the last years, due to the increased demand of accurate, dense and geo-referenced 3D data. Their main characteristic is the ability of acquiring 3D information of large areas dynamically. This versatility has expanded their application fields from the civil engineering to a broader range (industry, emergency response, cultural heritage...), which is constantly widening. This increased number of needs, some of them specially challenging, is pushing the Scientific Community, as well as companies, towards the development of innovative solutions, ranging from new hardware / open source software approaches and integration with other devices, up to the adoption of artificial intelligence methods for the automatic extraction of salient features and quality assessment for performance verification The aim of the present book is to cover the most relevant topics and trends in Mobile Mapping Technology, and also to introduce the new tendencies of this new paradigm of geospatial science"vi
dc.description.tableofcontents"About the Special Issue Editors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . vii Preface to ”Mobile Mapping Technologies” . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ix Qing Li, Jiasong Zhu, Rui Cao, Ke Sun, Tao Liu, Jonathan M. Garibaldi, Qingquan Li and Guoping Qiu Indoor Topological Localization Using a Visual Landmark Sequence Reprinted from: Remote Sens. 2019, 11, 73, doi:10.3390/rs11010073 . . . . . . . . . . . . . . . . . . 1 Runzhi Wang, Wenhui Wan, Kaichang Di, Ruilin Chen and Xiaoxue Feng A High-Accuracy Indoor-Positioning Method with Automated RGB-D Image Database Construction Reprinted from: Remote Sens. 2019, 11, 2572, doi:10.3390/rs11212572 . . . . . . . . . . . . . . . . . 25 KeWang, Xin Huang, JunLan Chen, Chuan Cao, Zhoubing Xiong and Long Chen Forward and Backward Visual Fusion Approach to Motion Estimation with High Robustness and Low Cost Reprinted from: Remote Sens. 2019, 11, 2139, doi:10.3390/rs11182139 . . . . . . . . . . . . . . . . . 45 Xuke Hu, Hongchao Fan, Alexey Noskov, Alexander Zipf, ZhiyongWang and Jianga Shang Feasibility of Using Grammars to Infer Room Semantics Reprinted from: Remote Sens. 2019, 11, 1535, doi:10.3390/rs11131535 . . . . . . . . . . . . . . . . . 69 Tao Liu, Xing Zhang, Qingquan Li, Zhixiang Fang and Nadeem Tahir An Accurate Visual-Inertial Integrated Geo-Tagging Method for Crowdsourcing-Based Indoor Localization Reprinted from: Remote Sens. 2019, 11, 1912, doi:10.3390/rs11161912 . . . . . . . . . . . . . . . . . 96 Dongsheng Yang, Shusheng Bi,WeiWang, Chang Yuan,WeiWang, Xianyu Qi and Yueri Cai DRE-SLAM: Dynamic RGB-D Encoder SLAM for a Differential-Drive Robot Reprinted from: Remote Sens. 2019, 11, 380, doi:10.3390/rs11040380 . . . . . . . . . . . . . . . . . 119 Guanci Yang, Zhanjie Chen, Yang Li and Zhidong Su Rapid Relocation Method for Mobile Robot Based on Improved ORB-SLAM2 Algorithm Reprinted from: Remote Sens. 2019, 11, 149, doi:10.3390/rs11020149 . . . . . . . . . . . . . . . . . 148 Hang Liu, Qin Ye, Hairui Wang, Liang Chen and Jian Yang A Precise and Robust Segmentation-Based Lidar Localization System for Automated Urban Driving Reprinted from: Remote Sens. 2019, 11, 1348, doi:10.3390/rs11111348 . . . . . . . . . . . . . . . . . 169 Samer Karam, George Vosselman, Michael Peter, Siavash Hosseinyalamdary and Ville Lehtola Design, Calibration, and Evaluation of a Backpack Indoor Mobile Mapping System Reprinted from: Remote Sens. 2019, 11, 905, doi:10.3390/rs11080905 . . . . . . . . . . . . . . . . . 187 Markus Hillemann, Martin Weinmann, Markus S. Mueller and Boris Jutzi Automatic Extrinsic Self-Calibration of Mobile Mapping Systems Based on Geometric 3D Features Reprinted from: Remote Sens. 2019, 11, 1955, doi:10.3390/rs11161955 . . . . . . . . . . . . . . . . 210 v Zhen Cao, Dong Chen, Yufeng Shi, Zhenxin Zhang, Fengxiang Jin, Ting Yun, Sheng Xu, Zhizhong Kang and Liqiang Zhang A Flexible Architecture for Extracting Metro Tunnel Cross Sections from Terrestrial Laser Scanning Point Clouds Reprinted from: Remote Sens. 2019, 11, 297, doi:10.3390/rs11030297 . . . . . . . . . . . . . . . . . 239 Manuel Rodr´ıguez-Mart´ın, Pablo Rodr´ıguez-Gonz´alvez, Esteban Ruiz de O˜ na Crespo and Diego Gonz´alez-Aguilera Validation of Portable Mobile Mapping System for Inspection Tasks in Thermal and Fluid–Mechanical Facilities Reprinted from: Remote Sens. 2019, 11, 2205, doi:10.3390/rs11192205 . . . . . . . . . . . . . . . . . 261 Andrea di Filippo, Luis Javier S´anchez-Aparicio, Salvatore Barba, Jos´e Antonio Mart´ın-Jim´enez, Roc´ıo Mora and Diego Gonz´alez Aguilera Use of a Wearable Mobile Laser System in Seamless Indoor 3D Mapping of a Complex Historical Site Reprinted from: Remote Sens. 2018, 10, 1897, doi:10.3390/rs10121897 . . . . . . . . . . . . . . . . . 280 Ana del-Campo-Sanchez, Miguel Moreno, Rocio Ballesteros and David Hernandez-Lopez Geometric Characterization of Vines from 3D Point Clouds Obtained with Laser Scanner Systems Reprinted from: Remote Sens. 2019, 11, 2365, doi:10.3390/rs11202365 . . . . . . . . . . . . . . . . . 299 vi"vi
dc.language.isoenvi
dc.publisherMDPIvi
dc.subjectMobile laser scanningvi
dc.subjectPortable mobile mapping systemsvi
dc.subjectCalibrationvi
dc.subjectAirborne laser scanningvi
dc.subjectData fusionvi
dc.subjectSensor integrationvi
dc.subjectFeature extractionvi
dc.subject3D modellingvi
dc.subjectGeoreferencingvi
dc.subjectVerification and validationvi
dc.subjectAccuracy and precision assessmentvi
dc.titleMobile Mapping Technologiesvi
dc.typeBookvi
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SA11381_1. Mobile Mapping Technologies - Cover.pdf
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Cover708.8 kBAdobe PDFXem/Tải về  Yêu cầu tài liệu
SA11381_2. Mobile Mapping Technologies - Copyright.pdf
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Copyright515.94 kBAdobe PDFXem/Tải về  Yêu cầu tài liệu
SA11381_3. Mobile Mapping Technologies - index.pdf
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index520.2 kBAdobe PDFXem/Tải về  Yêu cầu tài liệu
SA11381_4. Mobile Mapping Technologies - Chap 1.pdf
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Indoor Topological Localization Using a Visual Landmark Sequence520.83 kBAdobe PDFXem/Tải về  Yêu cầu tài liệu
SA11381_5. Mobile Mapping Technologies - Chap 2.pdf
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A High-Accuracy Indoor-Positioning Method with Automated RGB-D Image Database Construction7.49 MBAdobe PDFXem/Tải về  Yêu cầu tài liệu
SA11381_6. Mobile Mapping Technologies - Chap 3.pdf
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Forward and Backward Visual Fusion Approach to Motion Estimation with High Robustness and Low Cost6.94 MBAdobe PDFXem/Tải về  Yêu cầu tài liệu
SA11381_7. Mobile Mapping Technologies - Chap 4.pdf
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Feasibility of Using Grammars to Infer Room Semantics11.15 MBAdobe PDFXem/Tải về  Yêu cầu tài liệu
SA11381_8. Mobile Mapping Technologies - Chap 5.pdf
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An Accurate Visual-Inertial Integrated Geo-Tagging Method for Crowdsourcing-Based Indoor Localization1.47 MBAdobe PDFXem/Tải về  Yêu cầu tài liệu
SA11381_9. Mobile Mapping Technologies - Chap 6.pdf
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DRE-SLAM: Dynamic RGB-D Encoder SLAM for a Differential-Drive Robot3.8 MBAdobe PDFXem/Tải về  Yêu cầu tài liệu
SA11381_10. Mobile Mapping Technologies - Chap 7.pdf
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Rapid Relocation Method for Mobile Robot Based on Improved ORB-SLAM2 Algorithm62.47 MBAdobe PDFXem/Tải về  Yêu cầu tài liệu
SA11381_11. Mobile Mapping Technologies - Chap 8.pdf
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A Precise and Robust Segmentation-Based Lidar Localization System for Automated Urban Driving3.01 MBAdobe PDFXem/Tải về  Yêu cầu tài liệu
SA11381_12. Mobile Mapping Technologies - Chap 9.pdf
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Design, Calibration, and Evaluation of a Backpack Indoor Mobile Mapping System8.76 MBAdobe PDFXem/Tải về  Yêu cầu tài liệu
SA11381_13. Mobile Mapping Technologies - Chap 10.pdf
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Automatic Extrinsic Self-Calibration of Mobile Mapping Systems Based on Geometric 3D Features3.38 MBAdobe PDFXem/Tải về  Yêu cầu tài liệu
SA11381_14. Mobile Mapping Technologies - Chap 11.pdf
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A Flexible Architecture for Extracting Metro Tunnel Cross Sections from Terrestrial Laser Scanning Point Clouds42.22 MBAdobe PDFXem/Tải về  Yêu cầu tài liệu
SA11381_15. Mobile Mapping Technologies - Chap 12.pdf
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Validation of Portable Mobile Mapping System for Inspection Tasks in Thermal and Fluid–Mechanical Facilities16.67 MBAdobe PDFXem/Tải về  Yêu cầu tài liệu
SA11381_16. Mobile Mapping Technologies - Chap 13.pdf
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Use of a Wearable Mobile Laser System in Seamless Indoor 3D Mapping of a Complex Historical Site6.05 MBAdobe PDFXem/Tải về  Yêu cầu tài liệu
SA11381_17. Mobile Mapping Technologies - Chap 14.pdf
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Geometric Characterization of Vines from 3D Point Clouds Obtained with Laser Scanner Systems7.57 MBAdobe PDFXem/Tải về  Yêu cầu tài liệu
SA11381_18. Mobile Mapping Technologies - Chap 15.pdf
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Geometric Characterization of Vines from 3D Point Clouds Obtained with Laser Scanner Systems7.23 MBAdobe PDFXem/Tải về  Yêu cầu tài liệu


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