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Face verification and recognition for digital forensics and information security

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

Details

Original languageEnglish
Title of host publication7th International Symposium on Digital Forensics and Security, ISDFS 2019
EditorsAsaf Varol, Murat Karabatak, Cihan Varol, Sevginur Teke
PublisherIEEE
ISBN (Electronic)9781728128276
DOIs
Publication statusPublished - 1 Jun 2019
Publication typeA4 Article in a conference publication
EventInternational Symposium on Digital Forensics and Security - Barcelos, Portugal
Duration: 10 Jun 201912 Jun 2019

Conference

ConferenceInternational Symposium on Digital Forensics and Security
CountryPortugal
CityBarcelos
Period10/06/1912/06/19

Abstract

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.

Keywords

  • Deep learning, Face verification, Forensics, Security, Surveillance

Publication forum classification

Field of science, Statistics Finland