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Gesture recognition method and device and electronic equipment

A gesture recognition and gesture technology, applied in neural learning methods, electrical digital data processing, biological neural network models, etc., can solve problems such as difficulty in meeting huge vocabulary recognition, insufficient expression ability, etc., to eliminate dimensional effects and improve accuracy. rate effect

Active Publication Date: 2020-05-05
SHENZHEN POLYTECHNIC
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  • Claims
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Problems solved by technology

[0004] In view of this, the embodiment of the present application provides a gesture recognition method, device and electronic equipment to solve the lack of expressive ability of the gesture recognition system in the prior art in the case of sequence characteristics and big data recognition, and it is difficult to meet the huge vocabulary. identified technical deficiencies

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  • Gesture recognition method and device and electronic equipment
  • Gesture recognition method and device and electronic equipment

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Embodiment Construction

[0046] In the following description, specific details such as specific system structures and technologies are presented for the purpose of illustration rather than limitation, so as to thoroughly understand the embodiments of the present application. It will be apparent, however, to one skilled in the art that the present application may be practiced in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, devices, circuits, and methods are omitted so as not to obscure the description of the present application with unnecessary detail.

[0047]The gesture recognition method provided in this application proposes to learn the mapping relationship between the EMG signal sequence and the gesture through the long-term short-term memory network LSTM, including using the characteristics of the long-term dependence of the network to learn the relationship in the EMG signal sequence, and using its good at The characteristics ...

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Abstract

The invention provides a gesture recognition method and device and electronic equipment, and the method comprises the steps: enabling an MYO gesture control armlet to serve as electromyographic signalcollection equipment to obtain a to-be-recognized electromyographic signal, and enabling the to-be-recognized electromyographic signal to be a one-dimensional time sequence signal; preprocessing theto-be-identified electromyographic signal to generate to-be-input data used for identification operation; and inputting the to-be-input data into a preset gesture recognition model for recognition soas to obtain a gesture action label having a mapping relationship with the to-be-recognized electromyographic signal, with the gesture recognition model being constructed and generated by taking a long short-term memory network LSTM as a base learner. The gesture recognition model is constructed by taking a long short-term memory network LSTM as a base learner, so that the problems of insufficientexpression ability and large vocabulary quantity for gesture recognition of sequence characteristics and big data and difficulty in meeting recognition requirements are solved, and the accuracy of gesture recognition is improved.

Description

technical field [0001] The present application belongs to the technical field of gesture recognition and deep learning model construction, and in particular relates to a gesture recognition method, device and electronic equipment. Background technique [0002] Sign language is an indispensable means of communication for the hearing-impaired and speech-impaired. However, because most normal people are not familiar with sign language, people with language impairments and ordinary people cannot communicate freely face to face when communicating, which makes communication still very difficult. In terms of providing real-time sign language recognition and translation for the hearing-impaired and speech-impaired, limited by the difficulty of gesture recognition, there is still a lack of mature technical solutions in the market. [0003] At present, most of the existing gesture recognition systems based on electromyographic signals use hidden Markov HMM for gesture modeling and re...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F3/01G06N3/04G06N3/08
CPCG06F3/015G06N3/084G06N3/044G06N3/045
Inventor 袁辉何跃军李钊华
Owner SHENZHEN POLYTECHNIC
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