3D gesture recognition method and system based on a deep convolutional neural network

Abstract

The invention provides a 3D gesture recognition method and system based on a deep convolutional neural network. The method comprises the steps that firstly, using a first deep convolutional neural network or conducting pre-segmentation on a large number of color images containing hands, and extracting hand action parts; secondly, performing hand joint node detection on the extracted hand by usinga second deep convolutional neural network; Performing gesture 3D reconstruction on the detected joint nodes by using a double-flow deep convolutional network; And finally, constructing a softmax network comprising three full connection layers to identify the 3D reconstructed gesture. The technical scheme provided by the invention has the beneficial effects that the gesture recognition precision can be effectively improved. From the perspective of application range, an object of the method is an RGB image collected by a monocular camera, required equipment is simple and cheap, and the application scene is wider.

Description

technical field [0001] The present invention relates to the field of deep learning, in particular to a 3D gesture recognition method and system based on a deep convolutional neural network. Background technique [0002] 70% of human perception of the objective world is obtained by vision. Using computers to replace humans to perceive, semantically analyze and understand the world is the ultimate goal of computer vision. As one of the most natural ways of communication for human beings, gestures have a strong function of information expression and transmission. The act of manipulating with hands is the main way for people to interact with the outside world. The problem of gesture recognition mainly comes from the demand of new human-computer interaction technology. It is an indispensable and important part of new human-computer interaction technology and has broad application prospects. Applying gesture recognition to the smart home field, people can use gestures to control...

AI Technical Summary

Problems solved by technology

This kind of gesture detection based on optical images has the following problems: it cannot overlap with human body parts with similar skin color such as hands, it is easily affected by illumination changes, and it is difficult to achieve effective segmentation in complex backgrounds; in the era of big data, traditional image methods are difficult to cope with massive data, relying too much on manual features or intuitive and simple features

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