Dynamic gesture recognition method and device

Abstract

The invention discloses a dynamic gesture recognition method and device, which can acquire multiple gesture images with continuous time frames, divide each gesture image into multiple image blocks, perform Fourier transform and skin color judgment changes on each image, and recognize gestures Image blocks and non-gesture image blocks, and then according to the identification values ​​of the gesture image blocks and non-gesture image blocks in the gesture images corresponding to adjacent time frames, logical operations are performed on the gesture images corresponding to adjacent time frames, and according to the logical operation results Gesture sliding recognition, due to the processing process of this method, does not need to process the entire image, and uses logical operations to simplify and integrate the relationship between multiple image blocks after the logo, so that gesture recognition can be performed quickly and accurately without occupying a large amount of memory resources, greatly improving the efficiency of gesture recognition.

Description

technical field [0001] The invention relates to the technical field of human-computer interaction, in particular to a dynamic gesture recognition method and device. Background technique [0002] The importance of gesture interaction in the field of human-computer interaction technology is becoming more and more prominent. In the scene based on virtual human-computer interaction, gestures are mainly used to complete the grasping, moving and releasing of different objects on the virtual interface. Therefore, a lot of dynamic Gestures are used to complete the operation of objects. In order to ensure the real-time performance of dynamic gesture recognition, it is necessary to quickly and accurately recognize dynamic gestures. [0003] In the prior art, gesture recognition is performed based on the Tower algorithm, and its calculation process is very complicated, and the amount of calculation is huge, which reduces the real-time performance of gesture recognition. For gesture re...

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Problems solved by technology

[0003] In the prior art, gesture recognition is performed based on the Tower algorithm, the calculation process is very complicated, and the amount of calculation is huge, which reduces the real-time performance of gesture recognition

For gesture recognition based on gesture training, if the gesture model is too simple in order not to occupy a large amount of memory, the accuracy of gesture recognition will be reduced; if in order to ensure the accuracy of gesture recognition, a large amount of training is required for the gesture model, and the increased variables will take up a lot memory

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