A Gait Recognition Method Based on Multilinear Mean Component Analysis

Abstract

The invention provides a gait recognition method based on multi-linear mean component analysis. The gait recognition method comprises a training stage and a recognition stage. The training stage refers to performing dimension reduction processing on a half-cycle gait sequence image subjected to linear interpolation through the following algorithms, and training to obtain a projection conversion matrix of the algorithms: projecting the half-cycle gait sequence image into a low-dimension multi-linear subspace through general tensor discriminant analysis; performing further feature extraction by adopting the multi-linear mean component analysis; enabling a training tensor sample to be finally projected into a low-dimension vector space by adopting linear discriminant analysis. According to the recognition stage, conversion matrixes obtained through training the to-be-recognized half-cycle gait sequence image sample with the general tensor discriminant analysis and multi-linear mean component analysis algorithms are subjected to twice projection in a tensor space, the conversion matrix obtained through training the to-be-recognized half-cycle gait sequence image sample with the linear discriminant analysis algorithm is projected in the vector space, and a nearest neighbor classifier is adopted in the vector space during recognition. The gait recognition method can be used for improving the accuracy of gait recognition and has high robustness under different environments.

Description

technical field [0001] The invention belongs to the field of machine learning and pattern recognition, and relates to a gait recognition method. [0002] technical background [0003] In recent years, with the rapid development of the economy, effective and reliable public safety and information security construction has become more and more popular in society. At present, identity verification using biometric features such as face, fingerprint, iris, and DNA has been popularized in many application fields. As an integral part of biological characteristics, gait recognition has attracted more and more attention from researchers in recent years. [0004] The purpose of gait recognition research is to identify people based on their walking gait characteristics without the subject being aware of it. It has the following advantages: First, it has low requirements for acquisition equipment and does not require a high-resolution acquisition system; second, it can realize long-dis...

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Problems solved by technology

[0005] Studies have shown that these multi-linear subspace learning algorithms can solve the dimensionality reduction problem of gait sequence images well, but there is still room for improvement in recognition performance

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