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首页> 外文会议>2019 7th International Symposium on Digital Forensics and Security >Face Verification and Recognition for Digital Forensics and Information Security
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Face Verification and Recognition for Digital Forensics and Information Security

机译：数字取证和信息安全的人脸验证和识别

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摘要

In this paper, we present an extensive evaluation of face recognition and verification approaches performed by the European COST Action MULTI-modal Imaging of FOREnsic SciEnce Evidence (MULTI-FORESEE). The aim of the study is to evaluate various face recognition and verification methods, ranging from methods based on facial landmarks to state-of-the-art off-the-shelf pre-trained Convolutional Neural Networks (CNN), as well as CNN models directly trained for the task at hand. To fulfill this objective, we carefully designed and implemented a realistic data acquisition process, that corresponds to a typical face verification setup, and collected a challenging dataset to evaluate the real world performance of the aforementioned methods. Apart from verifying the effectiveness of deep learning approaches in a specific scenario, several important limitations are identified and discussed through the paper, providing valuable insight for future research directions in the field.
机译：在本文中，我们介绍了由FORESTIC科学证据的欧洲COST动作多模式成像（MULTI-FORESEE）进行的人脸识别和验证方法的广泛评估。这项研究的目的是评估各种面部识别和验证方法，范围从基于面部标志的方法到最新的现成的预训练卷积神经网络（CNN）以及CNN模型直接针对即将完成的任务进行培训。为了实现这一目标，我们精心设计并实施了一个与典型的面部验证设置相对应的逼真的数据采集过程，并收集了一个具有挑战性的数据集来评估上述方法的真实性能。除了在特定情况下验证深度学习方法的有效性外，本文还确定并讨论了一些重要限制，从而为该领域的未来研究方向提供了宝贵的见识。

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  • 来源
  • 会议地点 Barcelos(PT)
  • 作者

    Giuseppe Amato; Fabrizio Falchi; Claudio Gennaro; Fabio Valerio Massoli; Nikolaos Passalis; Anastasios Tefas; Alessandro Trivilini; Claudio Vairo;

  • 作者单位

    Institute of Information Science and Technologies of the National Research Council of Italy (ISTI-CNR), via G. Moruzzi 1, Pisa, 56124, Italy;

    Institute of Information Science and Technologies of the National Research Council of Italy (ISTI-CNR), via G. Moruzzi 1, Pisa, 56124, Italy;

    Institute of Information Science and Technologies of the National Research Council of Italy (ISTI-CNR), via G. Moruzzi 1, Pisa, 56124, Italy;

    Institute of Information Science and Technologies of the National Research Council of Italy (ISTI-CNR), via G. Moruzzi 1, Pisa, 56124, Italy;

    Faculty of Information Technology and Communication Sciences, Tampere University, Tampere, Finland;

    Department of Informatics, Aristotle University of Thessaloniki, Thessaloniki, Greece;

    Department of innovative technologies, Digital forensics lab, University of Applied Sciences of Southern - Switzerland, Lugano, Switzerland;

    Institute of Information Science and Technologies of the National Research Council of Italy (ISTI-CNR), via G. Moruzzi 1, Pisa, 56124, Italy;

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  • 原文格式 PDF
  • 正文语种 eng
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  • 关键词

    convolutional neural nets; data acquisition; digital forensics; face recognition; learning (artificial intelligence);

    机译：卷积神经网络;数据采集;数字取证;面部识别;学习（人工智能）;;

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