Investigating multi-touch gestures as a novel biometric modality

Napa Sae-Bae, Nasir Memon, Katherine Isbister

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We propose a new behavioral biometric modality based on multi-touch gestures. We define a canonical set of multi-touch gestures based on the movement characteristics of the palm and fingertips being used to perform the gesture. We developed an algorithm to generate and verify multi-touch gesture templates. We tested our techniques on a set of 22 different gestures. Employing a matching algorithm for a multi-touch verification system with a k-NN classifier we achieved 1.28% Equal Error Rate (EER). With score-based classifiers where only the first five samples of a genuine subject were considered as templates, we achieved 4.46 % EER. Further, with the combination of three commonly used gestures: pinch, zoom, and rotate, using all five fingers, 1.58% EER was achieved using a score-based classifier. These results are encouraging and point to the possibility of touch based biometric systems in real world applications like user verification and active authentication.

Original languageEnglish (US)
Title of host publication2012 IEEE 5th International Conference on Biometrics: Theory, Applications and Systems, BTAS 2012
Pages156-161
Number of pages6
DOIs
StatePublished - 2012
Event2012 IEEE 5th International Conference on Biometrics: Theory, Applications and Systems, BTAS 2012 - Arlington, VA, United States
Duration: Sep 23 2012Sep 27 2012

Other

Other2012 IEEE 5th International Conference on Biometrics: Theory, Applications and Systems, BTAS 2012
CountryUnited States
CityArlington, VA
Period9/23/129/27/12

Fingerprint

Biometrics
Classifiers
Authentication

ASJC Scopus subject areas

  • Computer Science Applications
  • Biomedical Engineering

Cite this

Sae-Bae, N., Memon, N., & Isbister, K. (2012). Investigating multi-touch gestures as a novel biometric modality. In 2012 IEEE 5th International Conference on Biometrics: Theory, Applications and Systems, BTAS 2012 (pp. 156-161). [6374571] https://doi.org/10.1109/BTAS.2012.6374571

Investigating multi-touch gestures as a novel biometric modality. / Sae-Bae, Napa; Memon, Nasir; Isbister, Katherine.

2012 IEEE 5th International Conference on Biometrics: Theory, Applications and Systems, BTAS 2012. 2012. p. 156-161 6374571.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Sae-Bae, N, Memon, N & Isbister, K 2012, Investigating multi-touch gestures as a novel biometric modality. in 2012 IEEE 5th International Conference on Biometrics: Theory, Applications and Systems, BTAS 2012., 6374571, pp. 156-161, 2012 IEEE 5th International Conference on Biometrics: Theory, Applications and Systems, BTAS 2012, Arlington, VA, United States, 9/23/12. https://doi.org/10.1109/BTAS.2012.6374571
Sae-Bae N, Memon N, Isbister K. Investigating multi-touch gestures as a novel biometric modality. In 2012 IEEE 5th International Conference on Biometrics: Theory, Applications and Systems, BTAS 2012. 2012. p. 156-161. 6374571 https://doi.org/10.1109/BTAS.2012.6374571
Sae-Bae, Napa ; Memon, Nasir ; Isbister, Katherine. / Investigating multi-touch gestures as a novel biometric modality. 2012 IEEE 5th International Conference on Biometrics: Theory, Applications and Systems, BTAS 2012. 2012. pp. 156-161
@inproceedings{d8aa140e9039441f9304e5034164a608,
title = "Investigating multi-touch gestures as a novel biometric modality",
abstract = "We propose a new behavioral biometric modality based on multi-touch gestures. We define a canonical set of multi-touch gestures based on the movement characteristics of the palm and fingertips being used to perform the gesture. We developed an algorithm to generate and verify multi-touch gesture templates. We tested our techniques on a set of 22 different gestures. Employing a matching algorithm for a multi-touch verification system with a k-NN classifier we achieved 1.28{\%} Equal Error Rate (EER). With score-based classifiers where only the first five samples of a genuine subject were considered as templates, we achieved 4.46 {\%} EER. Further, with the combination of three commonly used gestures: pinch, zoom, and rotate, using all five fingers, 1.58{\%} EER was achieved using a score-based classifier. These results are encouraging and point to the possibility of touch based biometric systems in real world applications like user verification and active authentication.",
author = "Napa Sae-Bae and Nasir Memon and Katherine Isbister",
year = "2012",
doi = "10.1109/BTAS.2012.6374571",
language = "English (US)",
isbn = "9781467313841",
pages = "156--161",
booktitle = "2012 IEEE 5th International Conference on Biometrics: Theory, Applications and Systems, BTAS 2012",

}

TY - GEN

T1 - Investigating multi-touch gestures as a novel biometric modality

AU - Sae-Bae, Napa

AU - Memon, Nasir

AU - Isbister, Katherine

PY - 2012

Y1 - 2012

N2 - We propose a new behavioral biometric modality based on multi-touch gestures. We define a canonical set of multi-touch gestures based on the movement characteristics of the palm and fingertips being used to perform the gesture. We developed an algorithm to generate and verify multi-touch gesture templates. We tested our techniques on a set of 22 different gestures. Employing a matching algorithm for a multi-touch verification system with a k-NN classifier we achieved 1.28% Equal Error Rate (EER). With score-based classifiers where only the first five samples of a genuine subject were considered as templates, we achieved 4.46 % EER. Further, with the combination of three commonly used gestures: pinch, zoom, and rotate, using all five fingers, 1.58% EER was achieved using a score-based classifier. These results are encouraging and point to the possibility of touch based biometric systems in real world applications like user verification and active authentication.

AB - We propose a new behavioral biometric modality based on multi-touch gestures. We define a canonical set of multi-touch gestures based on the movement characteristics of the palm and fingertips being used to perform the gesture. We developed an algorithm to generate and verify multi-touch gesture templates. We tested our techniques on a set of 22 different gestures. Employing a matching algorithm for a multi-touch verification system with a k-NN classifier we achieved 1.28% Equal Error Rate (EER). With score-based classifiers where only the first five samples of a genuine subject were considered as templates, we achieved 4.46 % EER. Further, with the combination of three commonly used gestures: pinch, zoom, and rotate, using all five fingers, 1.58% EER was achieved using a score-based classifier. These results are encouraging and point to the possibility of touch based biometric systems in real world applications like user verification and active authentication.

UR - http://www.scopus.com/inward/record.url?scp=84871989194&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84871989194&partnerID=8YFLogxK

U2 - 10.1109/BTAS.2012.6374571

DO - 10.1109/BTAS.2012.6374571

M3 - Conference contribution

SN - 9781467313841

SP - 156

EP - 161

BT - 2012 IEEE 5th International Conference on Biometrics: Theory, Applications and Systems, BTAS 2012

ER -