ScanVan Project : Images and 3D cloud points

The ScanVan project (2017-2021) aimed at demonstrating that Spherical Camera can greatly simplify the production of 3D photogrammetric datasets, allowing computing 3D models of cities on a daily basis. The initial phase of the project was conducted by two complementary teams, one at EPFL and one at HES-SO Valais. The EPFL team worked on the theoretical aspects and mathematical processing of algorithms that compute 3D scenes from spherical images and on the design the iterative process for doing the computation of large-scale graphs of connected scenes to process 3D models of an entire city. The HES-SO Valais team worked on the design and physical implementation of the system. In the course of the project, the research teams designed an omnidirectional central camera, an algorithm for geometry estimation that operates directly on spherical images and a densification technique based on the estimated geometry. The camera was mounted a vehicle and tested in the city of Sion.

The dataset  contains :

-   4 models of the same loop of Sion :
    
    -   a sparse model in ply format
    
    -   a dense model in ply format
    
    -   the sparse geo-registered model in the swiss coordinate system
        (EPSG:2056, CH1903+)
    
    -   the dense geo-registered model in the swiss coordinate system
        (EPSG:2056, CH1903+)

-   spherical images used for constructing this model, acquired with the ScanVan central omnidirectional camera. For privacy reasons, people and vehicles have been blurred. 

-   the *geodesy* folder contains
    
    -   a csv file listing the latitude and longitude of all images as
        positionned in the geo-registered model
    
    -   a text file listing the homologous points which were used to
        geo-register the model from its own coordinate system to the
        CH1903+ coordinates system

-   the script which produced the sparse and dense models and the
    output logs.

-   various outputs of the 3D sparse computation can be found in the
    *omvg* folder.