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From clothing to identity; manual and automatic soft biometrics

From clothing to identity; manual and automatic soft biometrics
From clothing to identity; manual and automatic soft biometrics
Soft biometrics have increasingly attracted research interest and are often considered as major cues for identity, especially in the absence of valid traditional biometrics, as in surveillance. In everyday life, several incidents and forensic scenarios highlight the usefulness and capability of identity information that can be deduced from clothing. Semantic clothing attributes have recently been introduced as a new form of soft biometrics. Although clothing traits can be naturally described and compared by humans for operable and successful use, it is desirable to exploit computer-vision to enrich clothing descriptions with more objective and discriminative information. This allows automatic extraction and semantic description and comparison of visually detectable clothing traits in a manner similar to recognition by eyewitness statements. This study proposes a novel set of soft clothing attributes, described using small groups of high-level semantic labels, and automatically extracted using computer-vision techniques. In this way we can explore the capability of human attributes vis-a-vis those which are inferred automatically by computer-vision. Categorical and comparative soft clothing traits are derived and used for identification/re identification either to supplement soft body traits or to be used alone. The automatically- and manually-derived soft clothing biometrics are employed in challenging invariant person retrieval. The experimental results highlight promising potential for use in various applications.
1556-6013
2377 - 2390
Jaha, Emad Sami
cc715fee-cbbf-4c20-a48a-a22a02d60387
Nixon, Mark S.
2b5b9804-5a81-462a-82e6-92ee5fa74e12
Jaha, Emad Sami
cc715fee-cbbf-4c20-a48a-a22a02d60387
Nixon, Mark S.
2b5b9804-5a81-462a-82e6-92ee5fa74e12

Jaha, Emad Sami and Nixon, Mark S. (2016) From clothing to identity; manual and automatic soft biometrics. IEEE Transactions on Information Forensics and Security, 11 (10), 2377 - 2390, [7498567]. (doi:10.1109/TIFS.2016.2584001).

Record type: Article

Abstract

Soft biometrics have increasingly attracted research interest and are often considered as major cues for identity, especially in the absence of valid traditional biometrics, as in surveillance. In everyday life, several incidents and forensic scenarios highlight the usefulness and capability of identity information that can be deduced from clothing. Semantic clothing attributes have recently been introduced as a new form of soft biometrics. Although clothing traits can be naturally described and compared by humans for operable and successful use, it is desirable to exploit computer-vision to enrich clothing descriptions with more objective and discriminative information. This allows automatic extraction and semantic description and comparison of visually detectable clothing traits in a manner similar to recognition by eyewitness statements. This study proposes a novel set of soft clothing attributes, described using small groups of high-level semantic labels, and automatically extracted using computer-vision techniques. In this way we can explore the capability of human attributes vis-a-vis those which are inferred automatically by computer-vision. Categorical and comparative soft clothing traits are derived and used for identification/re identification either to supplement soft body traits or to be used alone. The automatically- and manually-derived soft clothing biometrics are employed in challenging invariant person retrieval. The experimental results highlight promising potential for use in various applications.

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Accepted_EJaha&MSNixon_From Clothing to Identity.pdf - Accepted Manuscript
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More information

Accepted/In Press date: 9 June 2016
e-pub ahead of print date: 23 June 2016
Published date: October 2016
Organisations: Vision, Learning and Control

Identifiers

Local EPrints ID: 397019
URI: http://eprints.soton.ac.uk/id/eprint/397019
ISSN: 1556-6013
PURE UUID: 98fadb93-1797-4d02-9b18-7012cbb60d93
ORCID for Mark S. Nixon: ORCID iD orcid.org/0000-0002-9174-5934

Catalogue record

Date deposited: 27 Jun 2016 14:18
Last modified: 22 May 2020 00:23

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Contributors

Author: Emad Sami Jaha
Author: Mark S. Nixon ORCID iD

University divisions

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