Hand pose estimation based on active bone-conducted sound sensing
Hiroyuki Kato, Kentaro Takemura · 2016
Estimating hand poses is essential to achieve intuitive user interfaces. In Virtual Reality, an infrared (IR) camera is used for hand tracking, and direct manipulation can be accomplished by using hands. Additionally, wearable devices have also attracted attention because of their portability. We have developed a method based on the use of a wearable device to estimate the joint angle, which can be determined using the amplitude of vibration. However, the joint angle, which can be estimated, is limited to particular joints. Therefore, our proposed method determines the hand pose based on active bone-conducted sound sensing toward intuitive user interfaces. We employed the power spectral density as a feature, thereby enabling the hand pose to be classified with a support vector machine. We confirmed the recognition accuracy and the feasibility of our proposed method through evaluation experiments.