This is a cool example of the low-cost platform offered by the Raspberry Pi being used for inventive projects. The Raspberry Pi is a capable, low cost (Model B+ is £25GBP/$40USD) credit-card sized computer that was first released in February 2012. It was introduced to encourage computer science skills, particularly with students. This project sought to capture 3D depth maps by using stereo-pair cameras linked up to a Raspberry Pi Compute Module. Argon Design intern David Barker concocted a rig that processes stereoscopic depth maps from two cameras at a rate of 12FPS. The core functionality is provided by an algorithm well known in video compression: by splitting frames into blocks then comparing to blocks from other frames, you can detect motion and measure parallax, whilst taking advantage of real-time video processing capabilities. The story posted on the Raspberry Pi website has further details on how this was achieved, and the steps through which the algorithms were optimised to run in real-time.
The Raspberry Pi has been used in a separate instance to achieve 3D data capture through the construction of a spherical setup (using 40 Raspberry Pi + camera units) to capture entire body scans simultaneously. These two setups represent a means to achieving different results for different purposes: real-time applications tout immediate uses for robot vision, whilst applications that can be processed ‘offline’ are central to a host of data capture techniques creating accurate digital records of environments and objects, particularly those such as SfM photogrammetry and terrestrial laser scanning.