Automatic semantic face recognition
Automatic semantic face recognition
Recent expansion in surveillance systems has motivated research in soft biometrics that enable the unconstrained recognition of human faces. Comparative soft biometrics show superior recognition performance than categorical soft biometrics and have been the focus of several studies which have highlighted their ability for recognition and retrieval in constrained and unconstrained environments. These studies, however, only addressed face recognition for retrieval using human generated attributes, posing a question about the feasibility of automatically generating comparative labels from facial images. In this paper, we propose an approach for the automatic comparative labelling of facial soft biometrics. Furthermore, we investigate unconstrained human face recognition using these comparative soft biometrics in a human labelled gallery (and vice versa). Using a subset from the LFW dataset, our experiments show the efficacy of the automatic generation of comparative facial labels, highlighting the potential extensibility of the approach to other face recognition scenarios and larger ranges of attributes.
Face Recognition, soft biometrics, Attributes
Almudhahka, Nawaf, Yousef
929b4dbb-016d-44bb-9755-b9e0adb6ded0
Nixon, Mark
2b5b9804-5a81-462a-82e6-92ee5fa74e12
Hare, Jonathon
65ba2cda-eaaf-4767-a325-cd845504e5a9
29 June 2017
Almudhahka, Nawaf, Yousef
929b4dbb-016d-44bb-9755-b9e0adb6ded0
Nixon, Mark
2b5b9804-5a81-462a-82e6-92ee5fa74e12
Hare, Jonathon
65ba2cda-eaaf-4767-a325-cd845504e5a9
Almudhahka, Nawaf, Yousef, Nixon, Mark and Hare, Jonathon
(2017)
Automatic semantic face recognition.
The 12th IEEE International Conference on Automatic Face and Gesture Recognition, , Washington, United States.
30 May - 03 Jun 2017.
(doi:10.1109/FG.2017.31).
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Conference or Workshop Item
(Paper)
Abstract
Recent expansion in surveillance systems has motivated research in soft biometrics that enable the unconstrained recognition of human faces. Comparative soft biometrics show superior recognition performance than categorical soft biometrics and have been the focus of several studies which have highlighted their ability for recognition and retrieval in constrained and unconstrained environments. These studies, however, only addressed face recognition for retrieval using human generated attributes, posing a question about the feasibility of automatically generating comparative labels from facial images. In this paper, we propose an approach for the automatic comparative labelling of facial soft biometrics. Furthermore, we investigate unconstrained human face recognition using these comparative soft biometrics in a human labelled gallery (and vice versa). Using a subset from the LFW dataset, our experiments show the efficacy of the automatic generation of comparative facial labels, highlighting the potential extensibility of the approach to other face recognition scenarios and larger ranges of attributes.
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FG-soton-paper
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More information
Accepted/In Press date: 23 January 2017
e-pub ahead of print date: 29 June 2017
Published date: 29 June 2017
Venue - Dates:
The 12th IEEE International Conference on Automatic Face and Gesture Recognition, , Washington, United States, 2017-05-30 - 2017-06-03
Keywords:
Face Recognition, soft biometrics, Attributes
Organisations:
Vision, Learning and Control, Electronics & Computer Science
Identifiers
Local EPrints ID: 410731
URI: http://eprints.soton.ac.uk/id/eprint/410731
PURE UUID: 461a6c69-d40d-4388-8d7b-14ce0b20a2ac
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Date deposited: 09 Jun 2017 09:31
Last modified: 16 Mar 2024 05:14
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Contributors
Author:
Nawaf, Yousef Almudhahka
Author:
Jonathon Hare
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