Figure 1: GravitySpace recognizes people and objects. We use a mirror-metaphor to show how GravitySpace identifies users and tracks their location and poses, solely based on the pressure imprints they leave on the floor.

Smart rooms support users by offering not only a series of convenient functions, like home automation, but also by acting pro-actively on the user’s behalf. To this end, such rooms need to know their own geometry as well as the people and their actions within it. 

Figure 2: GravitySpace sees the scene from Figure 1 as a set of contacts (circles, lines, and text added for clarity).

We propose to use high-resolution pressure-sensitive floors as new approach for tracking people and furniture in smart rooms. While the floor is limited to sensing direct contact with its surface, we can conclude what takes place in the room above, such as users’ poses or collisions with virtual objects.

Figure 4: The GravitySpace prototype senses pressure at 1mm resolution and projects across an active area of 8 m² in a single seamless piece--a 10x larger version of multitoe.

To explore our approach and to demonstrate our vision true to scale, we have created an 8 m² back-projected floor prototype, termed GravitySpace, a set of passive touch-sensitive furniture, as well as algorithms for identifying users, furniture, and poses.

GravitySpace is a research project by Alan Bränzel, Daniel Hoffmann, Marius Knaust, Patrick Lühne, René Meusel, and Stephan Richter supervised by Christian Holz, Dominik Schmidt, and Patrick Baudisch at the Human Computer Interaction Lab at Hasso Plattner Institute.