Point Cloud Rendering
Point cloud rendering is a computer graphics technique for visualizing 3D data represented as a collection of points (a point cloud), where each point has spatial coordinates and often attributes like color or intensity. It is used to display large-scale 3D datasets, such as those from LiDAR scans, photogrammetry, or 3D sensors, without converting them to traditional mesh models. This approach is efficient for rendering massive datasets in applications like geospatial mapping, autonomous vehicles, and cultural heritage preservation.
Developers should learn point cloud rendering when working with large, unstructured 3D data from sources like LiDAR, where mesh conversion is computationally expensive or loses detail. It is essential for real-time applications in fields such as surveying, robotics, and virtual reality, where accurate spatial representation and performance are critical. Use cases include visualizing city models for urban planning, processing sensor data for self-driving cars, and creating interactive 3D models of historical sites.