Exploring pointing and other gestures for appliance control

Increasing numbers of networked appliances are bringing about new opportunities for control and automation. At the same time, an increase in multifunctional appliances is creating a complex and often frustrating environment for the end-user. Lighting control is a striking example; in an office or conference environment, a centralized control panel represents a group of devices. These panels are unintuitive because the mapping and grouping are unclear. Motivated by these opportunities and challenges, we are exploring the potential for sensor fusion to increase usability and improve user experience while retaining the user in the control loop. We have developed a novel, camera-less, multi-sensor solution for intuitive gesture-based indoor lighting control, called RElight. Using a wireless handheld device, the user simply points at a light fixture to select it and rotates his hand to continuously configure the dimming level. Pointing is a universal gesture that communicates one's interest in or attention to an object. Advanced machine learning algorithms allow rapid training of gestures and continuous control that supplements gesture classification.

Principle Investigator: Joseph Paradiso

Research Group: Responsive Environments group at the MIT Media Lab

Research Assistants: Nan Zhao, Brian Mayton

Postdoctoral Research Fellow: Nick Gillian