Non-contact gesture control method for music player

Abstract

The invention discloses a non-contact gesture control method for a music player. The non-contact gesture control method comprises the following steps: designing a gesture type; acquiring gesture information by using a millimeter wave radar, and extracting receiving antenna data; performing signal processing on the radar original echo to obtain a speed-time spectrogram; establishing a dual-channel convolutional neural network, and performing feature extraction on the two speed-time spectrograms through the dual-channel convolutional neural network; fusing the extracted features to obtain new features; predicting gesture information through the trained gesture classification model and outputting a Data value corresponding to a gesture category; and the music player controls and executes a corresponding function according to the Data value. According to the invention, the millimeter wave radar sensor is adopted to collect and output gesture information, the all-day and all-weather working capability is realized, the anti-interference capability is high, tiny actions can be captured under a dark condition, the problems that the gesture cannot be accurately recognized due to weak light and the cost of a required high-definition camera is high are solved, and the safety of a user is improved. Good market prospects are realized.

Description

technical field [0001] The invention belongs to the field of gesture recognition and millimeter wave radar, relates to radar signal processing and gesture recognition technology, and in particular relates to a non-contact gesture control method for a music player. Background technique [0002] Most of the gesture recognition and control related technologies are based on camera gesture control. The camera is used to capture hand movements, input the gesture recognition module of the computer to recognize the hand movements, and then control the program on the computer according to the recognition results. This camera-based gesture recognition technology has some problems in practical applications. On the one hand, the performance requirements of the camera are relatively high, otherwise the hand movements cannot be accurately recognized, which increases the production cost; on the other hand, the camera captures gestures. There are certain requirements for light, and it canno...

AI Technical Summary

Problems solved by technology

This camera-based gesture recognition technology has some problems in practical applications. On the one hand, the performance requirements of the camera are high, otherwise hand movements cannot be accurately recognized, which increases production costs; The light has certain requirements, and it cannot be recognized when the light is weak or blocked by obstacles

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