Search Results for "point clouds"

...The platform for fast and accurate multi-sensor data annotation. Label in-house or with an external workforce. Intuitive labeling interfaces for images, videos, and 3D point clouds (lidar and RGBD). Obtain segmentation labels, vector labels, and more. Our labeling interfaces are set up to label fast and precise. Powerful ML assistance lets you label faster and reduce costs. Integrate data labeling into your existing ML pipelines and workflows using our simple yet powerful Python SDK. Onboard your own workforce or use one of our workforce partners. ...

This software is designed to help users visualize and analyze 3D point clouds with an associated real value, in a fast and flexible fashion. The primary use is in Atom Probe Tomography, which is an atomic imaging technique. However the program may also be useful in other areas, such as geospatial data, lidar, etc.

A new algorithm for extracting roof tops was developed. Using the assumption that roof tops are planar in construction, a new approach was developed using volume of point clouds to determine whether a cluster contains planar points. This approach yields very promising results and with attention applied to its weaknesses, should provide another algorithm which can rival currently available roof top detection methods.

The intention behind this Lidar Visualisation Toolbox is to provide an easy-to-use, stand-alone application to create visualisations from high-resolution airborne LIDAR-based digital elevation data. LiVT also includes tools like raster file creation from xyz point clouds. A few mouse clicks and some processing time should be enough to go from an xyz ASCII file to a grey-scale SVF image, an LRM map or a percentage map of cumulative visibility. As LiVT does not include a data viewer, additional software will be necessary to display the processing results.

displaz is a cross platform viewer application for displaying LiDAR point clouds and high level features deduced from such point clouds. The interface and internals are optimised for viewing airborne laser scans of geographic data, but should also work for medium sized point clouds taken from other sources.