Hand Gesture Interaction with a Low-Resolution Infrared Image Sensor on an Inner Wrist

Abstract

We propose a hand gesture interaction method using a low-resolution infrared image sensor on an inner wrist. We attach the sensor to the strap of a wrist-worn device, on the palmar side, and apply machine-learning techniques to recognize the gestures made by the opposite hand. As the sensor is placed on the inner wrist, the user can naturally control its direction to reduce privacy invasion. Our method can recognize four types of hand gestures: static hand poses, dynamic hand gestures, finger motion, and the relative hand position. We developed a prototype that does not invade surrounding people's privacy using an 8 x 8 low-resolution infrared image sensor. Then we conducted experiments to validate our prototype, and our results imply that the low-resolution sensor has sufficient capabilities for recognizing a rich array of hand gestures. In this paper, we introduce an implementation of a mapping application that can be controlled by our specified hand gestures, including gestures that use both hands.