Skatespots are very likely to vanish sometime. May it be because they get closed using constructional elements like skatestoppers or they get torn down completely because they don’t fit in the plans of city development. Or they just get out-dated and need a re-construction.
For a long time I have dealt with the photographic documentation of Skatespots and I’m always on the search to capture the entirety of such spots. This includes the skatespot with all its various geometric objects, transitions, gradients and edges, the roughness of the floor, the cracks and ripples - as well as its surrounding and how it is embedded in urban space. All these aspects together create the feeling a skateboarder has when exploring the site.
I started to use SFM/MVS to create 3D point clouds from multiple photographs capturing different views of an object. Using these 3D point clouds it is possible to capture a skatespot in its entirety using photographic means, that’s very exciting. New development in Software and Hardware enable the usage of SFM/MVS methods with an appealing quality and at reasonable cost.
The Colmap software and the availability of GPU processing power at reasonable price made it possible for me to use SFM/MVS for the skatespot reconstructions.
The project started June, 2018 and is still running.
Continuing collecting data of DIY skatespots and working on visualization and publication methods.
Got first results of various skatespots, from single benches to a whole plaza. The data aquisition and the processing of the data has been done within two days.
I got a dedicated computer for the computation of the 3D point clouds. It has two graphics card providing enough GPU resources to speed up my SFM/MVS workflow and to compute 3D models with a higher resolution.
After a successful reconstruction of an example location using a workflow based on free software, I started to focus on a routine processing of the 3D reconstructions.
I started research and evaluation of available free software to apply structure-from-motion/multi-view stereo methods.