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Reliable Gait Recognition Using 3D Reconstructions and Random Forests - An Anthropometric Approach

机译:使用三维重建和随机森林进行可靠的步态识别 - 一种人体测量方法

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摘要

Photogrammetric measurements of bodily dimensions and analysis of gait patterns in CCTV are important tools in forensic investigations but accurate extraction of the measurements are challenging. This study tested whether manual annotation of the joint centers on 3D reconstructions could provide reliable recognition. Sixteen participants performed normal walking where 3D reconstructions were obtained continually. Segment lengths and kinematics from the extremities were manually extracted by eight expert observers. The results showed that all the participants were recognized, assuming the same expert annotated the data. Recognition based on data annotated by different experts was less reliable achieving 72.6% correct recognitions as some parameters were heavily affected by interobserver variability. This study verified that 3D reconstructions are feasible for forensic gait analysis as an improved alternative to conventional CCTV. However, further studies are needed to account for the use of different clothing, field conditions, etc.
机译:闭路电视中人体尺寸的摄影测量和步态模式分析是法医调查的重要工具,但准确地提取测量结果却具有挑战性。这项研究测试了在3D重建上人工标注关节中心是否可以提供可靠的识别。 16名参与者进行了正常行走,并不断获得3D重建。八位专家观察员手动提取了四肢的节段长度和运动学信息。结果表明,假设同一位专家对数据进行了注释,则所有参与者均被识别。基于不同专家批注的数据进行的识别可靠性较低,无法实现72.6%的正确识别,因为某些参数受到观察者间差异的严重影响。这项研究证实了3D重建作为法医步态分析的可行方法,可以作为常规CCTV的改进替代方案。但是,需要进一步研究以说明不同衣服的使用,现场条件等。

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