Pedestrian motion mode recognition method based on deep hybrid model

Abstract

The invention provides a pedestrian motion mode recognition method based on a deep hybrid model. The method comprises: acquiring data of four mobile phone placement positions and seven daily pedestrian motion modes by using an acceleration sensor, a gyroscope and a magnetometer which are arranged in the smart phone; automatically extracting features by adopting a convolutional neural network (CNN), then performing dimension reduction processing on the extracted features through a principal component analysis method, and inputting a processed result into a hybrid model for recognition in an XGBoost learning mode. According to the method, the CNN serves as a trainable feature extractor capable of automatically obtaining features from input, PCA is used for reducing the dimension of high-dimensional feature data to reduce the calculated amount, the XGBoost serves as a recognizer on the top layer of the network to output a result, and high reliability of feature extraction and classification is effectively guaranteed.

Description

technical field [0001] The invention belongs to the technical field of inertial navigation motion pattern recognition, in particular to a pedestrian motion pattern recognition method based on a deep hybrid model. Background technique [0002] In recent years, with the continuous development and maturity of MEMS manufacturing technology, low-cost, small-size, and high-sensitivity sensors have been used in a large number of electronic devices, such as smart phones, personal laptops, etc., which makes acquiring and analyzing data change. more and more convenient and flexible. At the same time, due to the popularity of mobile phones, people have put forward higher requirements for their intelligence. Among them, the pedestrian movement pattern recognition technology based on the built-in sensors of mobile phones has attracted widespread attention in the fields of indoor positioning, health monitoring, and smart cities. Therefore, how to realize high-precision pedestrian motion...

AI Technical Summary

Problems solved by technology

[0005] Aiming at the above-mentioned deficiencies in the prior art, a pedestrian motion pattern recognition method based on a deep hybrid model provided by the present invention solves the disadvantages of traditional manual extraction of pedestrian motion features, fully taps the rich feature data information contained in different signals, and reduces The problem of loss of original feature information

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