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首页> 外文会议>IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications >Automatic Face Recognition for Forensic Identification of Persons Deceased in Humanitarian Emergencies
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Automatic Face Recognition for Forensic Identification of Persons Deceased in Humanitarian Emergencies

机译：自动面临人道主义紧急情况下死者的法医识别

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摘要

Forensic scientists often need to identify deceased people. The identification process mainly consists of the analysis of the DNA, dental records, and physical appearance. In humanitarian emergencies, the antemortem documentation needed for forensic analyses may be limited. In this context, face recognition plays a relevant role since antemortem pictures of missing persons are commonly made available by their families. Therefore, automatic recognition systems could be of paramount importance for reducing the search time in databases of face images and for providing a second opinion to the scientists. However, there are only few preliminary studies on automatic face recognition methods for forensic applications, and none of the works in the literature consider problems related to humanitarian emergencies. In this paper, we propose the first study on automatic face recognition for humanitarian emergencies. Specifically, we propose a recognition methodology and we analyze the accuracy of different biometric methods based on deep learning strategies for a real study case. In particular, the considered data regard recent deaths of migrants in Mediterranean Sea. The obtained results are satisfactory, and suggest that automatic recognition methods based on deep learning strategies could be effectively adopted as support tools for forensic identification.
机译：法医科学家经常需要识别死者。鉴定过程主要包括分析DNA，牙科记录和外观。在人道主义紧急情况下，法医分析所需的防弹文件可能有限。在这种情况下，自家人通常可以通过他们的家人常常提供以来，人脸识别起着相关角色。因此，自动识别系统可以对减少面部图像数据库中的搜索时间并向科学家提供第二种意见来实现至关重要的重要性。然而，对法医应用的自动面部识别方法只有很少的初步研究，文献中没有任何作品考虑与人道主义紧急情况有关的问题。在本文中，我们提出了对人道主义紧急情况的自动面临自动面临的第一次研究。具体地，我们提出了一种识别方法，我们根据真实研究案例的深度学习策略分析不同生物方法的准确性。特别是，考虑的数据涉及地中海的移民近期死亡。获得的结果是令人满意的，并表明基于深度学习策略的自动识别方法可以有效地被用作法医识别的支持工具。

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