Abstract
We perform gesture recognition in a Virtual Reality (VR) environment using dataproduced by the Leap Motion device. Leap Motion generates a virtual three-dimensional (3D) handmodel by recognizing and tracking user‘s hands. From this model, the Leap Motion applicationprogramming interface (API) provides hand and finger locations in the 3D space. We present asystem that is capable of learning gestures by using the data from the Leap Motion device and theHidden Markov classification (HMC) algorithm. We have achieved the gesture recognitionaccuracy (mean ± SD) is 86.1 ± 8.2% and gesture typing speed is 3.09 ± 0.53 words per minute(WPM), when recognizing the gestures of the American Sign Language (ASL).
Subject
Fluid Flow and Transfer Processes,Computer Science Applications,Process Chemistry and Technology,General Engineering,Instrumentation,General Materials Science
Cited by
70 articles.
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