GravitySpace is a new approach to tracking people and objects indoors. Unlike traditional solutions based on cameras, GravitySpace reconstructs scene data from a pressure-sensing floor.
While the floor is limited to sensing objects in direct contact with the ground, GravitySpace reconstructs contents above the ground by first identifying objects based on their texture and then applying inverse kinematics. To explore our approach and to demonstrate our vision true to scale, we have created an 8m² back-projected floor prototype, termed GravitySpace, a set of passive touch-sensitive furniture, as well as algorithms for identifying users, furniture, and poses.
Further information:
http://www.hpi.uni-potsdam.de/baudisch
http://www.dominikschmidt.net/gravityspace