Facial Behaviometrics: the Case of Facial Deformation in Spontenaous Smile/Laughter

Stefanos Zafeiriou; Maja Pantic

doi:10.1109/CVPRW.2011.5981832

Facial Behaviometrics: the Case of Facial Deformation in Spontenaous Smile/Laughter

Stefanos Zafeiriou
, Maja Pantic

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

12 Citations (Scopus)

Abstract

In this paper we explore the use of dense facial deformation in spontaneous smile/laughter as a biometric signature. The facial deformation is calculated between a neutral image (as neutral we define the least expressive image of the smile/laughter episode) and the apex of spontaneous smile/laughter (as apex we define the frame of the maximum facial change/deformation) and its complex representation is regarded. Subsequently, supervised and unsupervised complex dimensionality reduction techniques, namely the complex Principal Component Analysis (PCA) and the complex Linear Discriminant Analysis (LDA), are applied at the complex vector fields for feature extraction. We demonstrate the efficacy of facial deformation as a mean for person verification in a database of spontaneous smiles/laughters.

Original language	Undefined
Title of host publication	IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops (CVPR-W 2011)
Place of Publication	USA
Publisher	IEEE
Pages	13-19
Number of pages	7
ISBN (Print)	978-1-4577-0529-8
DOIs	https://doi.org/10.1109/CVPRW.2011.5981832
Publication status	Published - Jun 2011
Event	24th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2011 - Colorado Springs, United States Duration: 20 Jun 2011 → 25 Jun 2011 Conference number: 24

Publication series

Name
Publisher	IEEE Computer Society

Conference

Conference	24th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2011
Abbreviated title	CVPR 2011
Country/Territory	United States
City	Colorado Springs
Period	20/06/11 → 25/06/11

Keywords

METIS-285027
IR-79433
Face Recognition
Databases
Humans
EWI-21325
Principal component analysis
Speech
Training
EC Grant Agreement nr.: ERC/203143
HMI-MI: MULTIMODAL INTERACTIONS
Vectors

Access to Document

10.1109/CVPRW.2011.5981832

http://eprints.eemcs.utwente.nl/secure2/21325/01/pantic_facial_behaviometrics.pdf

Cite this

@inproceedings{f9fd96a9cd6940f28cbfb04fdc2ff504,

title = "Facial Behaviometrics: the Case of Facial Deformation in Spontenaous Smile/Laughter",

abstract = "In this paper we explore the use of dense facial deformation in spontaneous smile/laughter as a biometric signature. The facial deformation is calculated between a neutral image (as neutral we define the least expressive image of the smile/laughter episode) and the apex of spontaneous smile/laughter (as apex we define the frame of the maximum facial change/deformation) and its complex representation is regarded. Subsequently, supervised and unsupervised complex dimensionality reduction techniques, namely the complex Principal Component Analysis (PCA) and the complex Linear Discriminant Analysis (LDA), are applied at the complex vector fields for feature extraction. We demonstrate the efficacy of facial deformation as a mean for person verification in a database of spontaneous smiles/laughters.",

keywords = "METIS-285027, IR-79433, Face Recognition, Databases, Humans, EWI-21325, Principal component analysis, Speech, Training, EC Grant Agreement nr.: ERC/203143, HMI-MI: MULTIMODAL INTERACTIONS, Vectors",

author = "Stefanos Zafeiriou and Maja Pantic",

note = "10.1109/CVPRW.2011.5981832 ; 24th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2011 ; Conference date: 20-06-2011 Through 25-06-2011",

year = "2011",

month = jun,

doi = "10.1109/CVPRW.2011.5981832",

language = "Undefined",

isbn = "978-1-4577-0529-8",

publisher = "IEEE",

pages = "13--19",

booktitle = "IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops (CVPR-W 2011)",

address = "United States",

}

Zafeiriou, S & Pantic, M 2011, Facial Behaviometrics: the Case of Facial Deformation in Spontenaous Smile/Laughter. in IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops (CVPR-W 2011). IEEE, USA, pp. 13-19, 24th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2011, Colorado Springs, Colorado, United States, 20/06/11. https://doi.org/10.1109/CVPRW.2011.5981832

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AU - Pantic, Maja

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PY - 2011/6

Y1 - 2011/6

N2 - In this paper we explore the use of dense facial deformation in spontaneous smile/laughter as a biometric signature. The facial deformation is calculated between a neutral image (as neutral we define the least expressive image of the smile/laughter episode) and the apex of spontaneous smile/laughter (as apex we define the frame of the maximum facial change/deformation) and its complex representation is regarded. Subsequently, supervised and unsupervised complex dimensionality reduction techniques, namely the complex Principal Component Analysis (PCA) and the complex Linear Discriminant Analysis (LDA), are applied at the complex vector fields for feature extraction. We demonstrate the efficacy of facial deformation as a mean for person verification in a database of spontaneous smiles/laughters.

AB - In this paper we explore the use of dense facial deformation in spontaneous smile/laughter as a biometric signature. The facial deformation is calculated between a neutral image (as neutral we define the least expressive image of the smile/laughter episode) and the apex of spontaneous smile/laughter (as apex we define the frame of the maximum facial change/deformation) and its complex representation is regarded. Subsequently, supervised and unsupervised complex dimensionality reduction techniques, namely the complex Principal Component Analysis (PCA) and the complex Linear Discriminant Analysis (LDA), are applied at the complex vector fields for feature extraction. We demonstrate the efficacy of facial deformation as a mean for person verification in a database of spontaneous smiles/laughters.

KW - METIS-285027

KW - IR-79433

KW - Face Recognition

KW - Databases

KW - Humans

KW - EWI-21325

KW - Principal component analysis

KW - Speech

KW - Training

KW - EC Grant Agreement nr.: ERC/203143

KW - HMI-MI: MULTIMODAL INTERACTIONS

KW - Vectors

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DO - 10.1109/CVPRW.2011.5981832

M3 - Conference contribution

SN - 978-1-4577-0529-8

SP - 13

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BT - IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops (CVPR-W 2011)

PB - IEEE

CY - USA

T2 - 24th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2011

Y2 - 20 June 2011 through 25 June 2011

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