The ability to co-opt everyday surfaces for touch interactivity has been an area of HCI research for several decades. Ideally, a sensor operating in a device (such as a smart speaker) would be able to enable a whole room with touch sensing capabilities. Such a system could allow for software-defined light switches on walls, gestural input on countertops, and in general, more digitally flexible environments. While advances in depth sensors and computer vision have led to step-function improvements in the past, progress has slowed in recent years. We surveyed the literature and found that the very best ad hoc touch sensing systems are able to operate at ranges up to around 1.5 m. This limited range means that sensors must be carefully positioned in an environment to enable specific surfaces for interaction. In this research, we set ourselves the goal of doubling the sensing range of the current state of the art system. To achieve this goal, we leveraged an interesting finger "denting" phenomena and adopted a marginal gains philosophy when developing our full stack. When put together, these many small improvements compound and yield a significant stride in performance. At 3 m range, our system offers a spatial accuracy of 0.98 cm with a touch segmentation accuracy of 96.1%, in line with prior systems operating at less than half the range. While more work remains to be done to achieve true room-scale ubiquity, we believe our system constitutes a useful advance over prior work.

Research Team: Vivian Shen, James Spann, and Chris Harrison

Awards: Best Paper