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Biometric Identification of Identical Twins: A Survey
Kevin W. Bowyer and Patrick J. Flynn,
IEEE 8th International Conference on Biometrics Theory, Applications and Systems (BTAS), September 2016.
pdf of this paper.
The ability of biometric techniques to distinguish
between identical twins is of interest for multiple reasons.
The research literature touching on this topic is spread
across a variety of areas. This survey pulls together the
literature to date in this area, identifies available datasets
for research, points out topics of uncertainty and suggests
possible future research.
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Kevin W. Bowyer,
Face Recognition and Identical Twins,
Invited Talk at Sixth IEEE Workshop on Analysis and Modeling of Faces and Gestures (AMFG 2015), June 12, 2015.
pdf of slides for this talk.
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Jeffrey R. Paone, Patrick J. Flynn, P. Jonathon Philips, Kevin W. Bowyer, Richard W. Vorder Bruegge, Patrick J. Grother, George W. Quinn, Matthew T. Pruitt and Jason M. Grant,
Double Trouble: Differentiating Identical Twins by Face Recognition,
IEEE Transactions in Information Forensics and Security 9 (2), 285-295, February 2014.
pdf of this paper.
Facial recognition algorithms should be able to operate even when similar-looking individuals
are encountered, or even in the extreme case of identical twins. An experimental data set
comprised of 17486 images from 126 pairs of identical twins (252 subjects) collected on the
same day and 6864 images from 120 pairs of identical twins (240 subjects) with images taken a
year later was used to measure the performance on seven different face recognition algorithms.
Performance is reported for variations in illumination, expression, gender, and age for both the
same day and cross-year image sets. Regardless of the conditions of image acquisition,
distinguishing identical twins are significantly harder than distinguishing subjects who are
not identical twins for all algorithms.
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A Study of Face Recognition of Identical Twins By Humans,
Soma Biswas, Kevin W. Bowyer and Patrick J. Flynn,
International Workshop on Information Forensics and Security (WIFS 2011), December 2011.
pdf of this paper.
In this work, we investigate human capability to distinguish between identical
twins. If humans are able to distinguish between facial images of identical twins,
it would suggest that humans are capable of identifying discriminiating facial
traits that can potentially be useful to develop algorithms for this very
challenging problem. Experiments with different viewing times and imaging
conditions are conducted to determine if humans viewing a pair of facial images can
perceive if the image pairs belong to the same person or to a pair of identical
twins. The experiments are conducted on 186 twin subjecs, making it the largest such
study in the literature to date.
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Twins 3D Face Recognition Challenge
Vipin Vijayan, Kevin W. Bowyer, Patrick Flynn, Di Huang, Liming Chen, Mark Hansen,
Omar Ocegueda, Shishir Shah, Ioannis Kakadiaris,
International Joint Conference on Biometrics (IJCB 2011), October 2011.
pdf of this paper.
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What Surprises Do Identical Twins Have for Identity Science?
Kevin W. Bowyer,
IEEE Computer 44(7), July 2011, 100-102.
Xplore link to this paper.
Experiments with biometric datasets from identical twins are helping to shape future
research in face and iris recognition.
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Genetically Identical Irises Have Texture Similarity That Is
Not Detected By Iris Biometrics
Karen Hollingsworth, Kevin W. Bowyer, Stephen Lagree, Samuel P. Fenker and Patrick J. Flynn,
Computer Vision and Image Understanding 115 (2011), 1493-1502.
pdf of this paper.
As the standard iris biometric algorithm "sees" them, the left and right irises
of the same person are as different as irises of unrelated people. Similarly,
in terms of iris biometric matching, the eyes of identical twins are as different
as irises of unrelated people.
The left and right eyes of an individual or the eyes of identical twins are
examples of genetically identical irises.
In experiments with human observers viewing pairs of iris images acquired using an
iris biometric system, we have found that there is recognizable similarity in
the left and right irises of an individual and the irises of identical twins.
This result suggests that iris texture analysis different from that performance in the
standard iris biometric algorithm may be able to answer questions that iris biometrics
cannot answer.
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Similarity of Iris Texture Identical Twins,
Karen Hollingsworth, Kevin W. Bowyer and Patrick J. Flynn,
IEEE Computer Society Workshop on Biometrics, June 2010, 22-29.
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Distinguishing Identical Twins By Face Recognition,
P. Jonathon Phillips, Patrick J. Flynn, Kevin W. Bowyer, Richard W. Vorder Bruegge,
Patrick J. Grother, George W. Quinn, Matthew Pruitt,
IEEE International Conference on Automatic Face and Gesture Recognition (FG 2011),
March 2011, 185-192.
pdf of this paper.
This paper measures ability of face recognition algorithms to distinguish between identical
twin siblings. The experimental dataset consists of images taken of 126 pairs of identical
twins (252 people) collected on the same day and 24 pairs of identical twins (48 people)
with images collected one year apart. Recognition experiments are conducted using three
of the top submissions to the Multiple Biometric Evaluation (MBE) 2010 Still Face Track. ...
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