A Data Glove Gesture Recognition Algorithm Based on Mathematical Statistics
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A data glove and gesture recognition technology, applied in computing, computer parts, character and pattern recognition, etc., can solve problems such as different degrees of flexion and extension of finger joints, inability to achieve matching, etc., to improve the accuracy of screening values, eliminate interference, Gesture recognition for precise effects
Active Publication Date: 2022-02-25
QINGHAI NORMAL UNIV
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[0010] Aiming at the deficiencies of the existing technology, the present invention provides a data glove gesture recognition algorithm based on mathematical statistics, which solves the problem that different users have different degrees of flexion and extension of finger joints, which leads to the inability to achieve relatively perfect matching.
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[0056]The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some, not all, embodiments of the present invention.
[0057] Examples of the described embodiments are shown in the drawings, wherein like or similar reference numerals designate like or similar elements or elements having the same or similar functions throughout. The embodiments described below by referring to the figures are exemplary and are intended to explain the present invention and should not be construed as limiting the present invention.
[0058] see figure 1 , is a flowchart of the present invention.
[0059] The process in this program is as follows:
[0060] Step 1: Based on the 20 one-handed mathematical gestures of hearing-impaired people, wear data gloves and use the sensor.getData() method under the Vi...
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Abstract
The invention discloses a data glove gesture recognition algorithm based on mathematical statistics, which relates to the technical field of artificial intelligence: including using the sensor.getData() method to divide the same gesture into a natural state and a stretched state to collect data Sensor angle value, save the value in two text files respectively. Read the values in the text document and store them in the arrays a1 and b1, a2 and b2, ..., a20 and b20, ai=(ai,1,ai,2,ai,3,...,ai,24) , bi=(bi,1,bi,2,bi,3,..,bi,24). The invention judges the offset degree and linear relationship between the randomly acquired gestures and the gestures in the template library by calculating the standard deviation and the correlation coefficient, and finds out the gestures most similar to the randomly acquired gestures in the template library. Through two screenings, the accuracy of the screening value is gradually improved, so that the gesture recognition is very precise. Moreover, the gesture recognition based on the data glove can eliminate the interference of the external environment.
Description
technical field [0001] The invention relates to the technical field of artificial intelligence, in particular to a data glove gesture recognition algorithm based on mathematical statistics. Background technique [0002] Gesture recognition technology is often used in sign language recognition and human-computer interaction. The process of gesture recognition is the process of classifying the trajectory points in the model parameter space of the hand into a certain subset of the space. Static gestures correspond to a point in the model parameter space, while dynamic gestures correspond to a trajectory in the model parameter space. Therefore, their identification methods are different. The existing gesture recognition technologies mainly include template matching method, neural network method, hidden Markov model method and so on. Among them, the neural network is a gesture recognition method based on vision. Hidden Markov model method is suitable for dynamic gesture recogn...
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