Use of photogrammetry and biomechanical gait analysis to identify individuals
Use of photogrammetry and biomechanical gait analysis to identify individuals
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使用摄影测量和生物力学步态分析来识别个体
DOI：
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发表时间：
2010
期刊：
影响因子：
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通讯作者：
N. Lynnerup
中科院分区：
文献类型：
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作者：
P. Larsen;E. Simonsen;N. Lynnerup
摄影测量和步态模式识别是基于监控记录帮助识别犯罪者的宝贵工具。我们已经发现，身高，但只有少数其他措施具有令人满意的重现性用于法医学。发现了几个具有高识别率的步态变量，特别是位于额面的变量，由于时间过程模式的个体间差异很大，因此是有趣的。具有高识别率的变量似乎更适合用于法医步态分析，并作为输入变量的波形分析技术，如主成分分析，导致边际分数，这是很难单独解释。最后，提出了一种新的步态模型的基础上，功能主成分分析与潜在的检测个人步态模式的时间过程中的模式可以直接解释的输入变量。本文将结合法医学案例对上述方法进行讨论。
Photogrammetry and recognition of gait patterns are valuable tools to help identify perpetrators based on surveillance recordings. We have found that stature but only few other measures have a satisfying reproducibility for use in forensics. Several gait variables with high recognition rates were found. Especially the variables located in the frontal plane are interesting due to large inter-individual differences in time course patterns. The variables with high recognition rates seem preferable for use in forensic gait analysis and as input variables to waveform analysis techniques such as principal component analysis resulting in marginal scores, which are difficult to interpret individually. Finally, a new gait model is presented based on functional principal component analysis with potentials for detecting individual gait patterns where time course patterns can be marginally interpreted directly in terms of the input variables. In this presentation, the above methods will be discussed exemplified with forensic cases.