Gait recognition method based on dynamic vision sensor

Abstract

The invention relates to the technical field of gait recognition, and discloses a gait recognition method based on a dynamic vision sensor. The invention creatively provides a spatiotemporal mode analysis method based on the dynamic vision sensor. Through an impulsive neural network model based on a Tempotron algorithm, the goal of training and recognizing gait data recorded by the dynamic vision sensor can be achieved, so that the finally obtained gait recognition has high biological authenticity; therefore the gait recognition can be performed on a plurality of objects; the problem of high difficultly of the gait detection in the complicated background can be solved; and the high accuracy of the gait recognition can be ensured. Meanwhile, the invention also provides two coding modes; the fast convergence can be realized in the training process; and the good recognition correctness rate is obtained. Particularly, by combining the fixed period mobile window data segment sample division mode, the correctness rate of the gait recognition can reach 85 percent or higher; the practical values are very high; and the practical popularization and application are convenient.

Description

technical field [0001] The invention relates to the technical field of gait recognition, in particular to a gait recognition method based on a dynamic visual sensor. Background technique [0002] At present, a large number of surveillance cameras have been installed in large-space buildings such as banks, shopping malls, airports, and subway stations, but manual surveillance methods cannot fully meet the current security needs, because it not only consumes a lot of manpower and financial resources , and the physiological visual fatigue of the monitoring personnel makes it difficult to achieve the purpose of safety warning. Therefore, these security-sensitive public places urgently need an intelligent early warning method. An ideal intelligent surveillance system should be able to automatically analyze the image data collected by the camera, and provide early warning before vicious events occur, thereby minimizing personal injury and economic loss. This requires the monitor...

AI Technical Summary

Problems solved by technology

[0007] Since gait recognition technology is still in its infancy, there are mainly the following difficulties: (1) In traditional gait recognition research, the basis of recognition can be formed by defining the kinematic parameters of human gait, but in gait Obvious limitations in the data acquisition process made it difficult to accurately identify and record all parameters affecting gait (even if the accuracy of measuring some gait parameters improved, it is still not known whether the acquisition of these parameters provided sufficient (2) The gait features captured by traditional cameras are easily affected or changed, that is, gait, as a biological feature, is easily affected and changed by various factors, such as clothing, Shoes, walking surface, walking speed, emotional state, physical condition, etc., and the truly effective features should try to have nothing to do with or be affected by these factors; (3) Gait detection in complex backgrounds is difficult, and most current The assumption of the gait recognition algorithm for the data acquisition environment is that the camera is stationary, only the observed person is moving in the field of view, and the background is usually static and uncomplicated. However, in practical applications, the background is usually complex, and the pedestrians in the field of view are often more than one

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