Human body posture recognition method based on convolutional neural network

Abstract

The invention discloses a human body posture recognition method based on a convolutional neural network. The method comprises the steps that original data of a mobile sensor are collected and labeled,data frequency down-sampling and normalization processing are conducted, a training set and a test set are divided, the convolutional neural network is trained, and a model is transplanted to an Android terminal for human body posture recognition. The method is used for human body posture recognition according to a convolutional neural network. According to the method, a Spit-Transform-Merge strategy is introduced into the implementation of the method; a group of Lego convolution kernels with a smaller channel number is provided, the convolution kernels are stacked according to a random mapping and cyclic matrix method so as to realize convolution operation, and finally, generated Lego feature maps are vertically combined and sent to a classifier through a full connection layer for sensordata identification. The method has the advantages of being high in recognition speed, high in recognition accuracy, small in calculation amount, high in generalization capacity and the like, and meanwhile the method plays a very important role in smart home, health detection, motion tracking and the like.

Description

Technical field [0001] The invention belongs to the field of intelligent monitoring of wearable equipment, and in particular relates to a human body gesture recognition method based on a convolutional neural network. Background technique [0002] In recent years, with the development of information technology and the popularization of intelligent technology, global technological changes are being further advanced, and technologies such as cloud computing, Internet of Things, big data and artificial intelligence are also developing rapidly. Among them, human body gesture recognition technology has begun to be widely used in computer vision related fields. Its application range is very wide, and it can be used in various fields such as human-computer interaction, film and television production, motion analysis, games and entertainment. People can use the human body gesture recognition to locate the motion trajectory of the human body joint points and record its motion data, and re...

AI Technical Summary

Problems solved by technology

[0006] Purpose of the invention: In response to the above problems, the purpose of the present invention is to provide a human body posture recognition method based on a smaller filter convolutional neural network for wearable devices, so as to get rid of the large computing load of the computer, the long computing time and accurate recognition. low degree problem

Images