Abstract
One of the keys to the success of interaction between people is communication. Communication can be done verbally or non-verbally. In this paper, we build interactions between humans and computers using hand gestures. The hand gesture is recognized by the palm of the hand which is obtained from the results of human skeleton segmentation through camera Kinect. Recognition of palm gestures is performed on a series of RGB Kinect output frames. Histogram of Oriented Gradient (HOG) is used to produce a palm frame per frame gesture feature which is arranged in 4 seconds as a gesture descriptor. Dynamic Time Warping (DTW) is used as a classifier that will compare the description of the input gesture with the template gesture description. Based on the results of the experiment, the performance of the hand gesture recognition system reached 76.7%.
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