Biometric Identification and Identical Twins Kevin W. Bowyer Computer Science and Engineering University of Notre Dame [email protected] 1 CSE X0537 - NOVEMBER 16, 2015. Twins and Identity Science Biology Biometrics Psychology How and to what extent are “identical twins” different ? What biometrics can tell “identical twins” apart, to what degree? How do people distinguish between “identical twins” ? 2 CSE X0537 - NOVEMBER 16, 2015. Distinguishing between pairs of identical twins is one the more challenging problems in face recognition. Klare, Paulino and Jain, Int. Joint Conf. Biometrics 2011. 3 CSE X0537 - NOVEMBER 16, 2015. https://www.youtube.com/watch?v=XGQAAs5quf4 (classic) https://www.youtube.com/watch?v=zV-Y0GBL5D8 (modern) 4 CSE X0537 - NOVEMBER 16, 2015. A detour through a computer scientist’s understanding of some biology about twins … 5 CSE X0537 - NOVEMBER 16, 2015. Frequency of Twins Ø Ø Ø Twin birth rate: 33.7 per 1,000 live births in US in 2013 (CDC stats). About ¾ of twins are “fraternal” and ¼ are “identical”. More frequent for older mothers, and with use of fertility drugs; becoming more frequent overall. 6 CSE X0537 - NOVEMBER 16, 2015. http://www.empr.com/news/overall-birth-rate-down-but-twin-deliveries-up/article/386846/ CSE X0537 - NOVEMBER 16, 2015. 7 Fraternal Twins Ø Ø Ø Ø Two different fertilized egg cells (zygotes) “Dizygotic” or DZ. No more genetically alike than nontwin siblings. (though they develop in the womb at the same time) Share 50% of genes. 8 CSE X0537 - NOVEMBER 16, 2015. “Identical” Twins Ø Ø Ø Fertilized egg cell splits into two. “Monozygotic” or MZ. Two individuals with same genetic makeup, But identical twins are not necessarily identical in appearance. 9 CSE X0537 - NOVEMBER 16, 2015. “Mirror” Identical Twins Ø Ø Ø Single fertilized egg cell splits later than regular identical (at 9-12 days). Physical asymmetries expressed opposite: left / right handed, mirrorimage dental irregularities, … About ¼ of MZ twins are mirror. 10 CSE X0537 - NOVEMBER 16, 2015. http://www.twin-pregnancy-and-beyond.com/mirror-twins.html CSE X0537 - NOVEMBER 16, 2015. 11 Even More Complicated … Ø Ø Ø Ø Identical twins can be monoamniotic or diamniotic. Identical twins can be monochorionic or dichorionic. (placenta) Monoamniotic is also monochorionic. Early-splitting zygotes are diamniotic and dichorionic. 12 CSE X0537 - NOVEMBER 16, 2015. Point to remember: Reports of 100% accuracy on images of a few sets of twins may be an accident of the twins being mirror twins. 13 CSE X0537 - NOVEMBER 16, 2015. A long-held truism of biometrics … By definition, identical twins cannot be distinguished based on DNA. Jain et al, On the similarity of identical twin fingerprints, Pattern Recognition, 2002. These twins are genetically identical, with the same chromosomes … they cannot be distinguished using the same DNA. Tao et al, Fingerprint Recognition with Identical Twin Fingerprints, PLoS ONE, 2012. 14 CSE X0537 - NOVEMBER 16, 2015. Turns out not to be true given the most recent DNA analysis techniques … 15 CSE X0537 - NOVEMBER 16, 2015. Where do you get biometric datasets of identical twins ? 16 CSE X0537 - NOVEMBER 16, 2015. www.twinsdays.org https://www.youtube.com/watch?v=uQJH64QyzPs CSE X0537 - NOVEMBER 16, 2015. 17 http://www3.nd.edu/~cvrl/CVRL/Data_Sets.html 18 CSE X0537 - NOVEMBER 16, 2015. How hard is it for face recognition algorithms to tell twins apart ? 19 CSE X0537 - NOVEMBER 16, 2015. Impostor distribution for images of non-twins Impostor distribution for images of twins 20 CSE X0537 - NOVEMBER 16, 2015. A to G = 3 top alg’s in MBE 2010 + 4 commercial. Baseline = Algorithm A with non-twin impostor pairs. CSE X0537 - NOVEMBER 16, 2015. 21 Best algorithm EER on twins is 13% to 17%. 22 CSE X0537 - NOVEMBER 16, 2015. Best algorithm EER of 9% to 16%. 23 CSE X0537 - NOVEMBER 16, 2015. Best algorithm EER of about 7% to 14%. CSE X0537 - NOVEMBER 16, 2015. 24 Best algorithm EER of about 15% to 16%. CSE X0537 - NOVEMBER 16, 2015. 25 Point to remember. Twin discrimination by face analysis is hard, with room for improvement that could help face recognition in general. 26 CSE X0537 - NOVEMBER 16, 2015. How do humans perform at distinguishing identical twins from face appearance ? 27 CSE X0537 - NOVEMBER 16, 2015. Twins or images of same person ? CSE X0537 - NOVEMBER 16, 2015. 28 Twins or images of same person ? CSE X0537 - NOVEMBER 16, 2015. 29 Twins or images of same person ? CSE X0537 - NOVEMBER 16, 2015. 30 Twins or images of same person ? CSE X0537 - NOVEMBER 16, 2015. 31 Twins or images of same person ? CSE X0537 - NOVEMBER 16, 2015. 32 Humans are more accurate than current face matching algorithms. CSE X0537 - NOVEMBER 16, 2015. 33 Humans do better with more time. CSE X0537 - NOVEMBER 16, 2015. 34 Humans appear to use skin markings as a major factor in this task. CSE X0537 - NOVEMBER 16, 2015. 35 Point to remember. Humans appear to learn to discriminate twins by interpreting skin marks in a “forensic” manner. (This interpretation is compatible with results by Sarah Stevenage, British Journal of Psychology, 2011.) 36 CSE X0537 - NOVEMBER 16, 2015. What about 3D face analysis for identical twins ? 37 CSE X0537 - NOVEMBER 16, 2015. 38 CSE X0537 - NOVEMBER 16, 2015. 39 CSE X0537 - NOVEMBER 16, 2015. Ø Ø Ø Ø Ø Minolta 910 with “tele” lens. About 100K points on face. 107 pairs of twins. Smile + neutral expression. “Same session” data. 40 CSE X0537 - NOVEMBER 16, 2015. Alg. 4 = I. Kakadiaris, U. of Houston’s “UR3D”. Good, but compare to performance on FRGC v2. CSE X0537 - NOVEMBER 16, 2015. 41 What about irises of identical twins ? 42 CSE X0537 - NOVEMBER 16, 2015. “… comparisons among the eyes of actual monozygotic twins also yielded a result expected for unrelated eyes ...” “How iris recognition works,” John Daugman, IEEE Trans CVST, 2004. 43 CSE X0537 - NOVEMBER 16, 2015. Verification of John Daugman’s claim. CSE X0537 - NOVEMBER 16, 2015. 44 Twins or Unrelated ? 45 CSE X0537 - NOVEMBER 16, 2015. Twins. 46 CSE X0537 - NOVEMBER 16, 2015. Twins or Unrelated ? 47 CSE X0537 - NOVEMBER 16, 2015. Unrelated. 48 CSE X0537 - NOVEMBER 16, 2015. Twins or Unrelated ? 49 CSE X0537 - NOVEMBER 16, 2015. Twins. 50 CSE X0537 - NOVEMBER 16, 2015. Twins or Unrelated ? 51 CSE X0537 - NOVEMBER 16, 2015. Unrelated. 52 CSE X0537 - NOVEMBER 16, 2015. Twins or Unrelated ? 53 CSE X0537 - NOVEMBER 16, 2015. Twins. 54 CSE X0537 - NOVEMBER 16, 2015. Twins or Unrelated ? 55 CSE X0537 - NOVEMBER 16, 2015. Unrelated. 56 CSE X0537 - NOVEMBER 16, 2015. Ø 76 pairs of twins, plus non-twins. Ø Image pair presented for 3 sec. Ø 5-point response scale. Ø Ø Over 80% accurate in twins / non-twin classification. 92% - 93% accuracy for “certain” responses. 57 CSE X0537 - NOVEMBER 16, 2015. Point to remember. Humans readily perceive iris texture similarity that current iris recognition technology does not. 58 CSE X0537 - NOVEMBER 16, 2015. What about fingerprints of identical twins ? 59 CSE X0537 - NOVEMBER 16, 2015. Jain, Prabhakar and Pankanti, On the similarity of identical twin fingerprints, Pattern Recognition 35, 2653-2663, 2002. CSE X0537 - NOVEMBER 16, 2015. 60 Essence of Jain et al conclusions: Ø Ø Ø Twin prints match more closely than those of unrelated persons. Twin prints very likely to have same print category: whorl, … Twin prints may be like matching unrelated person prints within the same category. 61 CSE X0537 - NOVEMBER 16, 2015. Jain, Prabhakar and Pankanti, On the similarity of identical twin fingerprints, Pattern Recognition 35, 2653-2663, 2002. 62 CSE X0537 - NOVEMBER 16, 2015. Point to remember. Fingerprints do allow reliable means of distinguishing between identical twins. 63 CSE X0537 - NOVEMBER 16, 2015. Twins studies have been done for various additional modalities: Ø Speaker identification Ø Handwriting Ø Gait Ø Ear Ø … 64 CSE X0537 - NOVEMBER 16, 2015. Limitations of biometric studies of twins to date include: Ø Ø Ø Ø “Small” size of dataset Over-focus on identical twins without fraternal twins, siblings Lack of verified MZ status Focus on one or a small number of biometrics 65 CSE X0537 - NOVEMBER 16, 2015. Questions ? 66 CSE X0537 - NOVEMBER 16, 2015. Figures and tables in this talk are borrowed from: J. R. Paone, et al, Double Trouble: Differentiating Identical Twins by Face Recognition, IEEE Trans. Info. Forensics and Security 9 (2), 285-295, February 2014. http://www3.nd.edu/~kwb/PaoneEtAlTIFS_2014.pdf S. Biswas et al, A Study of Face Recognition of Identical Twins By Humans, Int’l Workshop on Information Forensics and Security (WIFS 2011), December 2011. http://www3.nd.edu/~kwb/BiswasBowyerFlynnWIFS_2011.pdf V. Vijayan, et al, Twins 3D Face Recognition Challenge, Int. Joint Conference on Biometrics, October 2011. http://www3.nd.edu/~kwb/VijayanEtAlIJCB_2011.pdf P. J. Phillips, et al, Distinguishing Identical Twins By Face Recognition, IEEE Int. Conf. on Automatic Face and Gesture Recognition (FG 2011), March 2011, 185-192. http://www3.nd.edu/~kwb/PhillipsEtAlFG_2011.pdf K.Hollingsworth, et al, Similarity of Iris Texture Identical Twins, IEEE CS Workshop on Biometrics, June 2010, 22-29. http://www3.nd.edu/~kwb/HollingsworthEtAlCVIU_2011.pdf K.W. Bowyer, What Surprises Do Identical Twins Have for Identity Science?, IEEE Computer 44 (7), July 2011, 100-102. 67 CSE X0537 - NOVEMBER 16, 2015.
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