Chen | Photogrammetry Principles and Applications | Buch | 978-0-443-51697-9 | www.sack.de

Buch, Englisch, 380 Seiten, Format (B × H): 152 mm x 229 mm

Chen

Photogrammetry Principles and Applications

Lidar 3D Point Cloud Intelligent Processing
Erscheinungsjahr 2026
ISBN: 978-0-443-51697-9
Verlag: Elsevier Science

Lidar 3D Point Cloud Intelligent Processing

Buch, Englisch, 380 Seiten, Format (B × H): 152 mm x 229 mm

ISBN: 978-0-443-51697-9
Verlag: Elsevier Science


Photogrammetry Principles and Applications: LiDAR 3D Point Cloud Intelligent Processing addresses the growing demand for advanced 3D point cloud processing in geospatial and Earth observation fields. With LiDAR technology playing a vital role in autonomous driving, smart cities, and environmental monitoring, this book offers a systematic overview of core algorithms, including 3D reconstruction, DEM generation, and semantic segmentation, utilizing cutting-edge artificial intelligence methods like deep learning and large language models. It combines foundational knowledge with practical case studies from diverse regions such as Toronto, Xiamen, and Nanjing, illustrating how these techniques are applied in real-world scenarios. The content spans hardware descriptions, software workflows, and algorithmic insights, making it suitable for both self-study and academic courses. Featuring templates, flow diagrams, step-by-step processes, and tables, the book ensures ease of cross-referencing and practical understanding. It empowers researchers, students, and industry professionals to process complex, massive point cloud data efficiently, leading to more accurate spatial analysis, environmental assessments, and urban planning. By integrating AI into traditional photogrammetric workflows, this volume paves the way for innovations in geospatial intelligence and autonomous systems.

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Autoren/Hrsg.


Weitere Infos & Material


1. Laser Scanners
2. Laser Registration
3. 3D reconstruction
4. Digital Elevation Models
5. Point cloud expression and description
6. Point clouds detection and tracking
7. Point clouds semantic segmentation
8. Point clouds instance segmentation
9. Point clouds interactive segmentation
10. Point clouds software
11. Application examples


Chen, Yiping
Yiping Chen is an Associate Professor at Sun Yat-sen University, China, specializing in mobile laser scanning data analysis, 3D point cloud computer vision, and autonomous driving. She has published over 70 peer-reviewed articles in leading journals such as ISPRS Journal of Photogrammetry and Remote Sensing, IEEE Transactions on Geoscience and Remote Sensing, and IEEE Transactions on Intelligent Transportation Systems. Her work has been presented at major conferences including CVPR, IGARSS, and ISPRS; and she received the 2020 Best Paper award from the Journal of Applied Geodesy.



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