This book provides the theory and methodology for 3D digitalization with point clouds and AI to better serve remote sensing, 3D vision, autonomous driving, metaverse, and other industries. It addresses various aspects of 3D geoinformation including data collection, fusion, interpretation, representation, and applications in different fields.
Point clouds from LiDAR and photogrammetry are vital and vast sources of geospatial information besides remote sensing imagery. This book provides the latest theory and methodology for point cloud processing with AI to better serve earth observation, 3D vision, autonomous driving, smart city, and geospatial information applications. It addresses various aspects of 3D geospatial information including data capturing, fusing, geocomputing, modeling, and applications with the latest AI point cloud methods. With the inclusion of numerous illustrations, diagrams, and practical applications, readers will better understand the point cloud, and its technical challenges, and learn how to utilize point cloud in different fields.
Features
- Provides in-depth point cloud processing pipeline, cutting-edge theory, and technology with AI.
- Includes many specific applications of point cloud in the geospatial field.
- Offers a comprehensive step-by-step guide from theory to application in point cloud processing.
- Includes ample supplementary materials including datasets, tools, and other online resources.
- Helps readers across many disciplines from, geospatial to engineering, understand the vast application of point clouds, and how to further generate new ideas and innovative thoughts.
This book is an excellent resource for researchers, academics, students, and professionals in a variety of fields including Geomatics, Remote Sensing, Cartography and Geographic Information Systems, Data Science, Geography, Earth Science, and more.
Part I: Introduction.
1. Introduction to Point Cloud.
2. Ubiquitous
Point Cloud. Part II: Introduction of Fusion and Enhancement.
3. Multiview
Point Clouds Registration.
4. Cross-Platform Points Clouds Registration.
5.
Point Clouds and Panoramic Images Registration. Part III: Introduction of
Detection and Segmentation.
6. 3D Object Detection.
7. Point Cloud Semantic
Segmentation.
8. Point Cloud Instance Segmentation. Part IV: Introduction of
Modeling and Analysis.
9. 3D Terrain Modeling.
10. 3D Building
Reconstruction.
11. 3D Road Reconstruction. Part V: Software and
Applications.
12. Point Cloud Processing Software Point2Model.
13.
Applications of Uniquitous Point Cloud.
14. Conclusion and Outlooks.
Dr. Bisheng Yang is a full professor in LidAR and photogrammetry at Wuhan University, China, and the director of State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing (LIESMARS). His research expertise includes LiDAR and UAV photogrammetry, point cloud processing, GeoAI, and GIS and remote sensing applications. He has been Co-Chair of Point Cloud Processing Workgroup in the Photogrammetry Commission of the International Society for Photogrammetry and Remote Sensing (ISPRS) since 2016. He also serves as Associate Editor of the ISPRS Journal of Photogrammetry and Remote Sensing. He is the recipient of many academic awards including the Carl Pulfrich Award (2019), and the Smart City Technology Innovation Award Gold Medal (2023).
Prof. Dr. Zhen Dong honorably received his B.E. and Ph.D. degrees in remote sensing and photogrammetry from Wuhan University in 2011 and 2018, respectively. After his graduation, he worked as a post-doctoral researcher at LIESMARS, Wuhan University for two years. In 2022, he was promoted to full professor at LIESMARS, Wuhan University for his outstanding works in intelligent spatial understanding. His research interest lies in the field of 3D computer vision, particularly 3D reconstruction, scene understanding, and point cloud processing, as well as their applications in intelligent transportation systems, digital twin cities, urban sustainable development, and robotics.
Dr. Fuxun Liang received his Ph.D. degree in remote sensing and photogrammetry from Wuhan University. He is currently a postdoctoral fellow in the LIESMARS at Wuhan University. His research interest lies in the field of point cloud processing and its applications in building and energy.
Dr Xiaoxin Mi received her B.E. and Ph.D. degrees in remote sensing and photogrammetry from Wuhan University in 2016 and 2023, respectively. She is currently a post-doctoral fellow at Wuhan University of Technology. Her research interests include point cloud classification and segmentation, and road infrastructure modeling.
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