All you need to know about point cloud processing

The AEC (Architecture, Engineering and Construction) sector is leveraging modern technologies to take giant leaps towards digitization. One such technology – point cloud has proven to be an essential tool for CAD, geographic mapping, BIM modeling & more. It’s becoming a necessary tool for civil engineers and contractors who seek more ease and efficiency while conducting land surveys.

A point cloud is a set of data points that represents resolution (object or space). It is nothing more than a collection of millions or billions of data points of an object’s surface coming from a scanner. Each point has its own set of X, Y and Z geometric coordinates and additional attributes. 

Point clouds are most often created using 3D laser scanners and LiDAR technology/techniques. Each point showcases a single laser scan measurement, which is then put together to form a detailed and precise representation of the surveyed area using a process called ‘registration.’

The point clouds are relatively easy to edit, display, and filter data. A computer does not have to care about the scale or rotation of data points. Only color and position are two things that matter for computation.

Point clouds are the non-invasive way to generate geometry to measure buildings or services properties. The scanning process doesn’t undergo stringent safety measures. So it doesn’t hinder normal operations for sites such as hospitals, schools, colleges, malls, sporting venues, and more. It offers to scan flexibility during downtime or off-hours. These measurements are precise and more detailed than anything otherwise survey technology can produce. 

There are hundreds of 3D file types available for 3D modeling. This may prove to be a significant concern for interoperability. Different scanners produce raw data in various formats. Other processing software is compatible with some file types and each software possesses diverse exporting potential. The advancement of BIM has helped us get a unified platform to collaborate with multiple file formats.

The point clouds play an essential role in a wide range of applications. So it not possible for one software company to own the whole process. The point cloud library (PCL), an open-source software, is free for commercial and research use. It is successfully compiled cross-platform and can be deployed on Linux, macOS, Windows, and Android/iOS. The PCL framework comprises several algorithms that include filtering, registration, feature estimation, surface reconstruction, model fitting & segmentation.

Point clouds are becoming more popular in a wide range of application areas. Data availability, density, accuracy and size of 3D point clouds are projected to increase in the upcoming years widely. The advancements in technology will push scanners and point clouds to realize this potential.

Laser scanning is a famous land surveying method that uses advanced sensors, Global Positioning Systems (GPS), photodetectors and receiver electronics mounted on a platform. It throws up to 500,000 pulses every second. Each component enables researchers in the point cloud collection process.

LIDAR is classified into two types— topographic and bathymetric. Topographic lidar generally measures distances on land using a near-infrared laser. In contrast, bathymetric lidar uses water-penetrating green light to assess seafloor and riverbed elevations.

LiDAR technology points a laser at a target surface on the ground or under the water. The surface bounces back the light to the LiDAR system. Technicians/ Surveyors analyze the reflected light records to measure the distance traveled. This information is then combined with the location and orientation of the LIDAR equipment. The GPS receivers and internal measurement systems are used to measure the data. It generates a set of three-dimensional spatial coordinates specifying coordinate values in the longitude (x), latitude (y), and elevation (z) that creates a combination called a point.

When land surveying with LIDAR, the equipment collects numerous data points using the evaluation methods described above; hence, this collection of facts is called a “point cloud.”

The advances are in LiDAR technology are opening up the potential to capture spatial data in a point cloud for numerous projects, looking for point cloud to CAD model conversion services to maximize the data value of your next project? Consider outsourcing an engineering company that uses advanced technology and adheres to industry codes & standards.