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A frequentist estimation of duplicate probability as a baseline for person identification from image and video material using anthropometric measurements

dc.contributor.authorHeinke,Florian
dc.contributor.authorHeuschkel,Marie-Luise
dc.contributor.authorLabudde,Dirk
dc.contributor.editorDemmler, Daniel
dc.contributor.editorKrupka, Daniel
dc.contributor.editorFederrath, Hannes
dc.date.accessioned2022-09-28T17:10:45Z
dc.date.available2022-09-28T17:10:45Z
dc.date.issued2022
dc.description.abstractVideo and image material is becoming increasingly ubiquitous thus its potential as evidence in forensic investigations is growing. Once faces are hidden however, the value of surveillance footage is restricted unless there is another biometric trait that can be observed by camera such as linear body measurements. There is much biological evidence for human body proportions exhibiting much individual variation. Nevertheless, the probability of there being two individuals that match in their respective proportions ultimately determines its usability for the assignment, exclusion and even identification of persons in the forensic domain. This work is concerned with approaches for duplicate probability estimations derived from anthropometric measures. Here, we present a novel frequentist estimation using a dataset of 340 individuals and their respective anthropometric measurements. Drawing on density kernel estimations of measurement dissimilarity, we propose the duplicate probability to be in the order of 10^−15 to 10^−8.en
dc.identifier.doi10.18420/inf2022_07
dc.identifier.isbn978-3-88579-720-3
dc.identifier.pissn1617-5468
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/39572
dc.language.isoen
dc.publisherGesellschaft für Informatik, Bonn
dc.relation.ispartofINFORMATIK 2022
dc.relation.ispartofseriesLecture Notes in Informatics (LNI) - Proceedings, Volume P-326
dc.subjectBiometric features
dc.subjectanthropometric measurements
dc.subjectduplicate probability
dc.titleA frequentist estimation of duplicate probability as a baseline for person identification from image and video material using anthropometric measurementsen
gi.citation.endPage98
gi.citation.startPage91
gi.conference.date26.-30. September 2022
gi.conference.locationHamburg
gi.conference.sessiontitleInternational Workshop On Digital Forensics (IWDF)

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