University of Washington (UW) computer scientists have built a low-cost gesture recognition system that uses low-power sensors to pick up TV signals as both a power source and the means for detecting a user's gesture command.
"This is the first gesture recognition system that can be implemented for less than a dollar and doesn't require a battery," said Shyam Gollakota, UW assistant professor of computer science and engineering.
The technology could allow sensors to be attached to household electronics, making it possible to interact with everyday objects using gestures and also connect them to the Internet and to each other for "Internet of Things" applications.
In operation, a small sensor placed on an electronic device such as a smartphone uses an ultra-low-power receiver to extract and classify gesture information from wireless transmissions around the user. When a person gestures with their hand, it changes the amplitude of the wireless signals in the air. The sensors then recognize unique amplitude changes created by specific gestures.
Unlike with gesture recognition already possible on some mobile devices, including the Samsung Galaxy S4 smartphone, users of the "AllSee" technology do not have to first manually enable the feature. Also, the S4 user needs to see the device for the gesture technology to work, and if left on, the gesture system quickly drains the phone's battery.
In contrast, the "AllSee" device, which consumes only tens of microwatts of power, allows the user to gesture at the phone in a pocket or handbag to change the volume or mute the phone without having to touch or see the phone.
AllSee's capabilities on smartphones and battery-free sensors were tested using eight different hand gestures such as pushing or pulling to zoom in and out. The prototype correctly identified the gestures more than 90 percent of the time when performed more than two feet away from the device. The response time was less than 80 microseconds—1,000 times faster than blinking an eye. A wake-up gesture discriminates between unintentional motions and actual gestures.
Funds for the research came from a Google Faculty Research Award and the Washington Research Foundation.
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