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PI Physik Instrumente - Space Qualified Steering LW 1-15 MR
Photonics Dictionary

point cloud

A point cloud is a set of data points in a three-dimensional coordinate system, where each point represents a specific location in space. These points are typically obtained through various sensing techniques such as lidar (light detection and ranging), photogrammetry, structured light scanning, or 3D scanning.

Each point in a point cloud is defined by its spatial coordinates (x, y, z), representing its position in three-dimensional space, as well as potentially additional attributes such as color, intensity, or reflectance value. These attributes provide additional information about the properties of the surface or object being scanned.

Point clouds are commonly used in various fields and applications, including:

3D modeling and visualization: Point clouds are used to create accurate three-dimensional models of objects, environments, or landscapes. These models find applications in architecture, urban planning, virtual reality, and computer graphics.

Surveying and mapping: Point clouds are used in surveying and mapping applications to capture detailed information about the terrain, buildings, infrastructure, and other features of interest. They are valuable for creating digital elevation models, topographic maps, and as-built documentation.

Reverse engineering and inspection: Point clouds are used in reverse engineering processes to capture the geometry of physical objects and create digital representations for analysis, modification, or reproduction. They are also used for quality control and inspection in manufacturing and industrial applications.

Augmented reality and robotics: Point clouds are used in augmented reality applications to overlay digital information onto real-world scenes. They are also used in robotics for navigation, localization, and obstacle detection in autonomous systems.

Environmental monitoring: Point clouds are used to monitor and analyze changes in natural landscapes, ecosystems, and environmental features such as glaciers, forests, and coastlines. They are valuable for studying environmental phenomena, assessing habitat quality, and monitoring changes over time.

Overall, point clouds provide a rich and detailed representation of three-dimensional space, enabling a wide range of applications across various fields of science, engineering, and technology.

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