Point Clouds
Point clouds are sets of data points in a coordinate system, typically representing the external surface of objects in 3D space, often captured by LiDAR, photogrammetry, or 3D scanners. They consist of millions of points with X, Y, Z coordinates and can include additional attributes like color, intensity, or normal vectors. Point clouds are fundamental in fields like computer vision, robotics, and geospatial analysis for modeling and analyzing real-world environments.
Developers should learn about point clouds when working on applications involving 3D reconstruction, autonomous vehicles, augmented reality, or geographic information systems (GIS), as they provide raw spatial data for object detection, mapping, and simulation. For example, in autonomous driving, point clouds from LiDAR sensors are used to perceive surroundings and navigate safely, while in architecture, they enable precise modeling of existing structures for renovation projects.