Flux Tensor’s VB3D software, for advanced 3D modeling, enables rapid generation of quantitative 3D models from images and video. VB3D is a scalable and optimized pipeline for 3D reconstruction for dense environments using multi-view stereo volumetric voting methodology to reconstruct and map 3D scenes and terrain. This is achieved through a visual change-mapping capability, allowing users/analysts to visualize a given location and rapidly detect structure and terrain changes. This capability includes automated acquisition, upload and processing of 3D data rendered using proprietary algorithms to generate quantitative 3D point clouds from aerial data without the need for ground-truthing or normalization.
VB3D uses a proprietary multi-view 3D reconstruction pipeline to generate accurate 3D point clouds using visible RGB aerial imagery to improve situational awareness. The resulting models can be used in modeling and GIS applications and enable direct measurements of terrain and objects at real-world scale with sub 1-meter relative accuracy. This capability can be used for regular and frequent change detection, adding quantitative measurements of terrain and object dimensions.
Flux Tensor’s VB3D solution was used to convert this example of arial photography to a dimensionally accurate 3D point cloud that includes metadata to enable quantitative analysis or scene reconstruction. This 3D reconstruction pipeline uses multiple oblique views and a novel volumetric weighted-voting-based surface likelihood map estimation algorithm to reconstruct city-scale 3D models of a few square kilometers.
Flux Tensor’s visualization software can be used in conjunction with VB3D or other 3D modeling pipelines, automating the process of stitching together multiple 3D models in the same spatial area. This is useful for large area data collection when high resolution models for an area of interest are required.
The image above shows the output for a city-wide scene generation using stitching and geo-registration to create a dimensionally accurate 3D scene, derived from 3D point clouds.
Flux Tensor’s 3D solution also offers a way to detect changes between two or more 3D models automatically. This helps Flux Tensor customers with a defense and intel focus or architecture/engineering focus automate and quickly detect mission-critical changes to the spatial data collected by ariel assets (e.g. aircraft, drones, etc.). The example below demonstrates how this is achieved using images of a single site captured at two different time points. Top Left: Shows an aerial image of a site under construction at timestamp 1. Top Right: Shows that same site under construction at timestamp 2. Bottom: Shows a 3D reconstruction of the site using VB3D and automatically identifies object and terrain changes and calculates the volumetric change to one of the terrain features.