Hosted by Eric Andelin CP, Senior Workflow Advisor, SimActive with guest speaker, Alamillo, Photogrammetry Specialist, SimActive


Podcast Announcement

With the rise of multi-camera sensors capturing both nadir and oblique imagery, 3D models are becoming a more accessible output. The ability to collect data with multiple looks at the ground allows for the creation of very dense point clouds. These point clouds can then be used as a basis to create 3D models having the form of texturized meshes.

Correlator3D version 10.4 adds improved 3D modeling capabilities and was designed to be compatible with future modeling industry improvements. Input data consists of imagery along with point clouds generated from either photogrammetry or lidar. This gives the user more flexibility from the start and potential time savings in processing. Guest David Alamillo joins us to discuss the best practices when creating 3D models in Correlator3D.


Specifically, listeners will learn the following:

• Understanding the optimal sensors for 3D modeling

• Generating the best point cloud possible from imagery

• Performing triangulation to generate a texturized mesh

• Using lidar point clouds for modeling rather than photogrammetry


Podden och tillhörande omslagsbild på den här sidan tillhör SimActive. Innehållet i podden är skapat av SimActive och inte av, eller tillsammans med, Poddtoppen.

Senast besökta

Pixels and Points

Episode #37 Creating 3D Models From Point Clouds With New Correlator3D Version 10.4

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