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

机译:步态识别中使用的2D静态特征和2D动态特征之间的关系

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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,静态和动态特征都用于定义对象的步态特征。在这项研究中,研究了静态和动态特征之间的关系的存在。相关系数用于分析从“布拉德福德大学多模态步态数据库大学”提取的特征之间的关系。这项研究包括来自19个主题的二维动态和静态特征。动态特征受到受检者关节(膝盖,大腿,肩膀和肘部)的时间旋转数据的傅立叶变换驱动的相位加权幅度的损害。结果得出结论,认为有11对特征与显着相关(p <0.05)。该结果表明静态特征和动力学特征之间存在统计关系,这挑战了一些类似研究的结果。这些结果为该领域的进一步研究提供了巨大的潜力,并可能有助于利用潜在数据创建步态信号。

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