Fall detection method based on hourglass convolution automatic coding neural network

Abstract

The invention discloses a fall detection method based on an hourglass convolution automatic coding neural network, and the method comprises the following steps: inputting a collected image into the trained hourglass convolution automatic coding neural network, and judging whether a target falls or not; wherein the hourglass convolution automatic coding neural network comprises an hourglass convolution encoder and a classifier; wherein the hourglass convolution encoder is obtained by replacing a convolution layer in the convolution automatic encoder with an hourglass unit, namely an hourglass convolution layer; and the hourglass convolution encoder comprising three hourglass convolution layers and three pooling layers. According to the invention, the convolution layer in the convolution automatic encoder is replaced by the hourglass unit, so that in a complex visual task, when the hourglass convolution automatic encoder neural network is used to extract the multi-scale features of the video image, the intermediate features with richer information can be obtained, and the accuracy of fall detection is improved.

Description

technical field [0001] The invention relates to a fall detection method based on an hourglass convolution automatic encoding neural network, which belongs to the technical field of video processing. Background technique [0002] With the increasing aging of the population, the number of elderly people living alone has also increased sharply, and intelligent video surveillance technology has gradually become a mainstream direction in practical applications. Fall detection technology mainly uses image processing technology to actively track human objects for behavior recognition and behavior analysis. In practical applications, it can save social medical resources, relieve social pressure, and ensure the quality of life of the elderly in their later years. In order to accurately and effectively detect falls in the smart home monitoring environment, it is of great significance to study fall detection methods that are robust to dynamic scenes. [0003] In order to effectively u...

AI Technical Summary

Problems solved by technology

[0005] The purpose of the present invention is to provide a fall detection method based on hourglass convolution auto-encoding neural network, which can effectively solve the problems in the prior art, especially the low accuracy of fall detection

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