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Imputing Human Descriptions in Semantic Biometrics

Imputing Human Descriptions in Semantic Biometrics
Imputing Human Descriptions in Semantic Biometrics
Human identification at a distance has received significant interest due to the ever increasing surveillance infrastructure. Biometrics such as face and gait offer a suitable physical attribute to uniquely identify people from a distance. When linking this with human perception, these biometrics suffer from the semantic gap which is the difference between how people and how biometrics represent and describe humans. Semantic biometrics bridges this gap, allowing conversions between gait biometrics and semantic descriptions. One possible application of semantic biometrics is to automatically search surveillance footage for a person who best matches a given semantic description - possibly obtained from an eyewitness report. We now exploit patterns and structure within the physical descriptions to be able to predict occluded or erroneous data, thereby widening application potential. We show how imputation techniques can be used to increase accuracy and robustness of automatic semantic annotation of gait signatures.
Reid, Daniel
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Nixon, Mark
2b5b9804-5a81-462a-82e6-92ee5fa74e12
Reid, Daniel
2a5d60ee-542b-45fb-82c8-6bf1189696b8
Nixon, Mark
2b5b9804-5a81-462a-82e6-92ee5fa74e12

Reid, Daniel and Nixon, Mark (2010) Imputing Human Descriptions in Semantic Biometrics. Multimedia in Forensics, Security and Intelligence.

Record type: Conference or Workshop Item (Other)

Abstract

Human identification at a distance has received significant interest due to the ever increasing surveillance infrastructure. Biometrics such as face and gait offer a suitable physical attribute to uniquely identify people from a distance. When linking this with human perception, these biometrics suffer from the semantic gap which is the difference between how people and how biometrics represent and describe humans. Semantic biometrics bridges this gap, allowing conversions between gait biometrics and semantic descriptions. One possible application of semantic biometrics is to automatically search surveillance footage for a person who best matches a given semantic description - possibly obtained from an eyewitness report. We now exploit patterns and structure within the physical descriptions to be able to predict occluded or erroneous data, thereby widening application potential. We show how imputation techniques can be used to increase accuracy and robustness of automatic semantic annotation of gait signatures.

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Published date: 29 October 2010
Venue - Dates: Multimedia in Forensics, Security and Intelligence, 2010-10-29
Organisations: Southampton Wireless Group

Identifiers

Local EPrints ID: 271623
URI: http://eprints.soton.ac.uk/id/eprint/271623
PURE UUID: 0949d7ec-e586-4751-9856-6a64dcbb4624
ORCID for Mark Nixon: ORCID iD orcid.org/0000-0002-9174-5934

Catalogue record

Date deposited: 13 Oct 2010 12:54
Last modified: 22 Oct 2019 00:58

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Contributors

Author: Daniel Reid
Author: Mark Nixon ORCID iD

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