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Gesture data collection glove and sign language gesture recognition method based on gesture data collection glove

A data collection and gesture recognition technology, applied in the field of gesture data collection gloves and sign language gesture recognition, can solve the problems of low recognition accuracy, inflexible finger movement, and low gesture recognition accuracy.

Active Publication Date: 2020-09-25
CHONGQING UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] Existing gesture recognition devices include smart watches, smart bracelets, and smart gloves. Watches and bracelets have the advantages of small size, light weight and easy to carry. The accuracy rate is not high; while traditional smart gloves solve the problem of low recognition accuracy caused by fewer sensors, but cannot overcome the shortcomings of large size, poor wearing comfort and inflexible finger movement

Method used

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  • Gesture data collection glove and sign language gesture recognition method based on gesture data collection glove
  • Gesture data collection glove and sign language gesture recognition method based on gesture data collection glove
  • Gesture data collection glove and sign language gesture recognition method based on gesture data collection glove

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Experimental program
Comparison scheme
Effect test

Embodiment 1

[0079] see Figure 1 to Figure 3 , Gesture data collection glove, including glove main body, finger cot, connecting belt 5, gyroscope 1, bending sensor 2, main control module 3, communication module 4, voltage stabilizing module. The gyroscope 1 is a nine-axis sensor.

[0080] The glove body covers the user's palm.

[0081] A gyroscope 1 , a main control module 3 and a communication module 4 are attached to the inner side of the glove body.

[0082] The gyroscope 1 collects 3-axis acceleration sensing signals, 3-axis gyroscope sensing signals, and 3-axis magnetometer sensing signals when the user's hand moves, and sends them to the main control module 3 .

[0083] The finger cot covers the user's finger joints.

[0084] Several bending sensors 2 are pasted on the inner side of the finger cuff. There is a one-to-one correspondence between the bending sensor 2 and the user's finger joints. A bending sensor 2 is pasted on a finger.

[0085] The bending sensor 2 collects ben...

Embodiment 2

[0091] see Figure 4 To Fig. 9, the sign language gesture recognition method based on gesture data collection gloves, comprises the following steps:

[0092] 1) The user wears gesture data collection gloves and makes gestures corresponding to g kinds of Chinese pinyin. g is a positive integer.

[0093] 2) During the user's gesture, the gyroscope 1 and the bending sensor 2 respectively collect the 3-axis acceleration sensing signal, 3-axis gyroscope sensing signal, 3-axis magnetometer sensing signal, finger joint bending The signal is sent to the main control module 3. The gyroscope 1 is a nine-axis sensor.

[0094] The main control module 3 sends the received 3-axis acceleration sensing signal, 3-axis gyroscope sensing signal, 3-axis magnetometer sensing signal, and finger joint bending signal to the host computer through the communication module 4 .

[0095] 3) The host computer stores the received 3-axis acceleration sensing signal, 3-axis gyroscope sensing signal, 3-axi...

Embodiment 3

[0138] The sign language gesture recognition method (i.e. the deaf-mute sign language recognition algorithm) based on the gesture data collection gloves comprises the following steps:

[0139] 1) The user wears gesture data collection gloves and makes gestures corresponding to g kinds of Chinese pinyin. g is a positive integer.

[0140] 2) During the user's gesture, the gyroscope 1 and the bending sensor 2 respectively collect the 3-axis acceleration sensing signal, 3-axis gyroscope sensing signal, 3-axis magnetometer sensing signal, finger joint bending The signal is sent to the main control module 3. The gyroscope 1 is a nine-axis sensor.

[0141] The main control module 3 sends the received 3-axis acceleration sensing signal, 3-axis gyroscope sensing signal, 3-axis magnetometer sensing signal, and finger joint bending signal to the host computer through the communication module 4 .

[0142] 3) The host computer stores the received 3-axis acceleration sensing signal, 3-ax...

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Abstract

The invention discloses a gesture data collection glove and a sign language gesture recognition method based on the gesture data collection glove. The glove comprises a glove body, fingerstalls, a nine-axis sensor, a bending sensor, a main control module, a communication module and a connecting band. The method comprises the following steps: considering the difference of each algorithm in machinelearning by using an ensemble learning method, and improving the problem that a single recognition algorithm cannot achieve the highest recognition accuracy of each atomic gesture.

Description

technical field [0001] The invention relates to the technical fields of smart wear, human-computer interaction and machine learning, in particular to a gesture data collection glove and a sign language gesture recognition method based on the gesture data collection glove. Background technique [0002] Gesture recognition is an important field of human-computer interaction. Gesture recognition can not only improve the language understanding and cognition level between humans and computers, but also help people with different language systems communicate through computers, including hearing-impaired people. Communication with people with normal hearing and communication between people with different native languages. [0003] Existing gesture recognition devices include smart watches, smart bracelets, and smart gloves. Watches and bracelets have the advantages of small size, light weight and easy to carry. The accuracy rate is not high; while traditional smart gloves solve th...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F3/01G06F3/0346G06K9/00G06K9/62G06N3/04G06N3/08G06N20/00
CPCG06F3/014G06F3/017G06F3/0346G06N3/084G06N20/00G06V40/28G06N3/045G06F18/24147G06F18/24155
Inventor 刘礼王珊珊冉孟元廖军
Owner CHONGQING UNIV
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