Human body movement recognition method based on convolutional neural network feature coding

Abstract

The invention provides a human body movement recognition method based on convolutional neural network feature coding and mainly aims to solve the problems of complicated calculation and low accuracy in the prior art. According to the implementation scheme, TV-L1 is utilized to obtain a video light steam graph; convolutional neural network coding, local feature accumulation coding, dimension-reducing whitening processing and VLAD vector processing are sequentially performed in a video space direction and a light stream movement direction, and space direction VLAD vectors and movement direction VLAD vectors are acquired; and information in the video space direction and information in the light steam movement direction are merged to obtain human body movement classification data, and then classification processing is performed. According to the method, convolutional features are subjected to local feature accumulation coding, so that the recognition rate is increased when complicated background data is processed, and the calculated amount is reduced; the features acquired by fusing video VLAD vectors and light stream VLAD vectors has higher robustness to environmental changes, and the method can be used for performing detection and recognition on human body movement in a monitoring video in areas such as a community, a shopping mall and a privacy occasion.

Description

Human Action Recognition Method Based on Convolutional Neural Network Feature Coding technical field The invention belongs to the technical field of image processing, and further relates to human action recognition based on deep learning, specifically a method for human action recognition based on convolutional neural network feature coding, which can be used in areas such as residential areas, hotels, shopping malls, and confidential places. Human motion detection and recognition in surveillance video. Background technique With the rapid development of science and technology and the continuous improvement of people's living standards, people are paying more and more attention to safety issues in life. Nowadays, video surveillance equipment is becoming more and more popular, and video surveillance equipment is installed in many places such as residential quarters, hotels, parking lots, shopping malls, intersections, companies, and confidential places. As the scale of vide...

AI Technical Summary

Problems solved by technology

The shortcomings of this method are that the calculation is large, resulting in slow speed, poor real-time performance, and the problem of trajectory drift.

The disadvantage of this method is that the time complexity is high, and it is easily affected by occlusion and human body differences, so the accuracy is not high, and it is suitable for the recognition of simple actions.

The disadvantage of this method is that the process is complex and is easily affected by occlusion and human body differences.

The existing human action recognition methods have high time complexity, large amount of calculation, poor real-time performance, and are easily affected by occlusion, light intensity changes and human body differences.

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