Foundations of 3D Geometric Data and Computer Vision

Three-dimensional data processing powers modern computer vision, spatial computing, robotics, and interactive environments. This course provides a structured introduction to acquiring, structuring, and analyzing 3D geometric information. You will begin with core mathematical foundations and data formats, progressing to real-world geometric processing workflows and modern representation methods. What you'll learn: Understand core 3D representations including point clouds, polygon meshes, and voxel grids; Learn key acquisition methods such as LiDAR, structured light, and multi-view stereo; Apply geometric filtering, registration, surface reconstruction, and segmentation techniques; Explore modern concepts in spatial computing and neural 3D representations; Practice analyzing 3D spatial data through structured written walkthroughs and exercises. The curriculum starts with essential terminology and geometric fundamentals before guiding you through standard processing pipelines and contemporary 3D vision concepts. This course is designed for beginners in computer vision, software engineering, and spatial computing, with no prior 3D geometry experience required. Start reading today to build a strong foundation in 3D computer vision.