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Prediction of user ’ s intention based on the hand motion recognition

Most methods proposed in the literature for predicting movements involved in a reach-to-grasp action by human being are designed using passive methods, i.e, by using a camera in front of the user. A novel approach to understand the user’s intentions with computer vision methods is proposed in this paper. Our solution performs a hand motion estimation using a wearable system. To realize such system, we employ a camera beneath the wrist to capture motion from the user’s perspective. To predict hand intentions, we characterize a hand-movement trough a Hidden-Markov Model framework. As main result, our system can predict the movement before the hand can reach an object with a performance near to 90% in average.