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A Gesture Recognition Method Based on Deep Learning

A gesture recognition and deep learning technology, applied in the field of gesture recognition, can solve the problems of low recognition accuracy, single gesture function, poor real-time performance, etc., and achieve the effect of improving the recognition rate, improving the accuracy, and being easy to handle.

Active Publication Date: 2021-12-10
DONGHUA UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0007] The technical problem to be solved by the present invention is: in the traditional gesture recognition algorithm, there are generally problems such as low recognition accuracy, poor stability, poor real-time performance, and single gesture function.

Method used

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  • A Gesture Recognition Method Based on Deep Learning
  • A Gesture Recognition Method Based on Deep Learning
  • A Gesture Recognition Method Based on Deep Learning

Examples

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Embodiment Construction

[0028] Below in conjunction with specific embodiment, further illustrate the present invention. It should be understood that these examples are only used to illustrate the present invention and are not intended to limit the scope of the present invention. In addition, it should be understood that after reading the teachings of the present invention, those skilled in the art can make various changes or modifications to the present invention, and these equivalent forms also fall within the scope defined by the appended claims of the present application.

[0029] Embodiments of the present invention relate to a gesture recognition method based on deep learning, such as figure 1 shown, including the following steps:

[0030] Step 1, using the gesture training set and test set to train the binarized convolutional neural network;

[0031] Step 2. After the original gesture image is collected, the original gesture image is preprocessed to remove the influence of light on the origin...

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Abstract

The present invention provides a gesture recognition method based on deep learning, which is characterized in that it comprises the following steps: using gesture training set and test set to train the binarized convolutional neural network; using the color information reflected by skin color, based on the color information Segment the preprocessed original image to extract the gesture outline; use the trained binary convolutional neural network to judge the gesture instructions corresponding to the gesture outline; locate the starting and ending points of the dynamic gesture corresponding to a series of gesture outlines, and use TLD The algorithm tracks the gesture trajectory, and the deviation in the tracking process is corrected using the Haar classifier, and then the HMM algorithm is used to identify dynamic gestures. The method provided by the invention can solve the problems of low recognition accuracy, poor stability, poor real-time performance, single gesture function and the like generally existing in traditional gesture recognition.

Description

technical field [0001] The invention relates to a gesture recognition method based on deep learning, which belongs to the technical field of gesture recognition. Background technique [0002] The emergence of computers has had an extremely important impact on human social production and daily life. On the one hand, it has greatly improved the efficiency of information processing, and on the other hand, it has promoted the development of intelligent life. Therefore, how to efficiently and conveniently interact with computers has become a research hotspot. [0003] With the development of social information technology, Human Computer Interaction (HCI) has become an important part of daily life. As a new human-computer interaction method, gesture recognition technology has broad application prospects in many fields: (1) digital life and entertainment. For example, in 2008, Ericsson launched a smart phone R520m, which collects user gesture information through its built-in came...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06K9/00G06F3/01G06K9/46G06K9/62G06T7/10
CPCG06F3/017G06T7/10G06T2207/10024G06V40/113G06V10/44G06V10/56G06F18/241G06F18/214
Inventor 董训锋陈镜超李国振马啸天
Owner DONGHUA UNIV