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The relationship between 2D static features and 2D dynamic features used in gait recognition

机译:步态识别2D静态特征与2D动态特征的关系

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In most gait recognition techniques, both static and dynamic features are used to define a subject's gait signature. In this study, the existence of a relationship between static and dynamic features was investigated. The correlation coefficient was used to analyse the relationship between the features extracted from the "University of Bradford Multi-Modal Gait Database". This study includes two dimensional dynamic and static features from 19 subjects. The dynamic features were compromised of Phase-Weighted Magnitudes driven by a Fourier Transform of the temporal rotational data of a subject's joints (knee, thigh, shoulder, and elbow). The results concluded that there are eleven pairs of features that are considered significantly correlated with (p<0.05). This result indicates the existence of a statistical relationship between static and dynamics features, which challenges the results of several similar studies. These results bare great potential for further research into the area, and would potentially contribute to the creation of a gait signature using latent data.
机译:在大多数步态识别技术中,静态和动态功能都用于定义受试者的步态签名。在这项研究中,研究了静态和动态特征之间的关系的存在。相关系数用于分析“布拉德福德大学多模态步态数据库”中提取的特征之间的关系。该研究包括来自19个科目的二维动态和静态特征。动态特征是由受试者关节的时间旋转数据(膝盖,大腿,肩部和肘部)的傅里叶变换驱动的相加权幅度。结果得出结论,有11对具有显着相关的特征(P <0.05)。该结果表明静态和动态特征之间存在统计关系,这挑战了几种类似研究的结果。这些结果对进一步研究进入该地区的巨大潜力,并且可能有助于使用潜在数据创建步态签名。

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