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Optimized-neural-network gesture-recognition human-computer interaction method based on GL

A neural network and gesture recognition technology, applied in the field of human-computer interaction based on data glove gesture recognition, can solve the problems of delay and long cycle, and achieve increased training quality, good convergence speed and approximation ability, real-time performance and control accuracy. improved effect

Inactive Publication Date: 2017-01-25
HARBIN UNIV OF SCI & TECH
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AI Technical Summary

Problems solved by technology

[0004] The technical problem to be solved by the present invention is to provide a human-computer interaction method based on GL optimized neural network gesture recognition, to solve the problems of delay and long cycle in the existing gesture recognition algorithm, and to realize the robot remote control system based on data gloves The real-time performance brings better operation experience and higher precision robot control equipment to the operator

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  • Optimized-neural-network gesture-recognition human-computer interaction method based on GL

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Embodiment Construction

[0016] The operator puts on data gloves to collect gesture data through the sensor, and inputs the data to the computer. The computer processes and analyzes the data, and then conducts network learning and training through the neural network optimized based on the GL algorithm, and finally applies the trained algorithm to the In the gesture recognition based on data gloves, the interaction with the virtual environment is realized to create conditions for giving full play to the natural flexibility of the hand, such as figure 1 Shown is the block diagram of the virtual hand interactive operating system based on the data glove.

[0017] The so-called GL-optimized neural network gesture recognition human-computer interaction method includes gesture definition, GL-optimized RBF network algorithm, and gesture extraction and matching.

[0018] The following steps are included in the gesture definition:

[0019] (1) Gesture data is collected through the sensors of the data glove. Th...

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Abstract

The invention relates to an optimized-neural-network gesture-recognition human-computer interaction method based on GL. Gestures of an operator are collected through a Data Glove14 Ultra data glove are collected, then the collected data is processed, an optimized neural network based on the GL algorithm is subjected to network learning training, finally, the trained algorithm is applied to gesture recognition based on the data glove, and teleoperation of the robot is achieved.

Description

technical field [0001] The invention relates to the technology in the field of intelligent recognition, in particular to a human-computer interaction method based on data glove gesture recognition. Background technique [0002] With the development of virtual reality technology, data gloves, as a natural and efficient human-computer interaction device, are widely used in many fields such as sign language recognition, robot control and remote virtual assembly, providing a new way of information interaction. The data glove collects gesture data through the sensor, and inputs the data to the computer. The computer processes and analyzes the data, so as to control the virtual hand with different gestures, realize the interaction with the virtual environment, and create a new environment for giving full play to the natural flexibility of the hand. condition. The current product can already use the sensor to accurately detect the bending degree of the finger in three-dimensional ...

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Application Information

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IPC IPC(8): G06F3/01G06N3/04G06N3/08G06N3/12G06K9/62
CPCG06F3/014G06N3/04G06N3/08G06N3/126G06F18/23
Inventor 李东洁李洋洋杨柳
Owner HARBIN UNIV OF SCI & TECH
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