Abstract
3D point clouds have gained widespread attention in recent years due to their importance in 3D computer vision. In this chapter, we briefly describe the fundamentals of 3D point clouds, starting with a formal definition and the process by which they are formed. We then introduce several other popular 3D representations like 3D meshes and voxel grids, and compare these representations with point clouds. We further discuss the common tasks encountered in point cloud processing, including point cloud registration, object classification, semantic segmentation, object detection, and point cloud odometry. Next, we present some common applications of point clouds. Finally, we present some of the datasets that are frequently used in the research and development of 3D point cloud processing methods and algorithms. Overall, this introductory chapter forms the basis for the further chapters, which delve deeper into point cloud processing methods and related techniques.
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Liu, S., Zhang, M., Kadam, P., Kuo, CC.J. (2021). Introduction. In: 3D Point Cloud Analysis. Springer, Cham. https://doi.org/10.1007/978-3-030-89180-0_1
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DOI: https://doi.org/10.1007/978-3-030-89180-0_1
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