Bootstrapper uses one or more depth cameras to observe the shoes of users interacting with the interactive table display, such as Microsoft Surface.
It then identifies users by matching camera images with a database of known shoe images. When multiple users interact, Bootstrapper associates touches with shoes based on hand orientation.
Baudisch claims the approach can be implemented using consumer depth cameras because shoes offer large distinct features such as colour and they shoes naturally align themselves with the ground, giving the system a well-defined perspective.
A study into the effectiveness of Bootstrapper reported that the system recognised participants from a database of 18 users with 89% accuracy, based on a single observed frame.
However, the power of Bootstrapper is diminished when users change their shoes or multiple users wear the same shoes.