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15Chapter 1PublicationsThe featured list spans over all published and to be published documents of the author. Noneof these publications appear in the Bibliography.JournalsA. Dantcheva and C. Velardo and A. D’Angelo and J.-L. Dugelay, “Bag of soft biometrics forperson identification. New trends and challenges,” Multimedia Tools and Applications, vol.51, no. 2, pp. 739 - 777, 2011.A. Dantcheva and J.-L. Dugelay, “Perception of Female Facial Beauty based on Anthropometric,Non Permanent and Acquisition Characteristics,” to be submitted.A. Dantcheva, P. Elia and J. L. Dugelay, “Human-like person re–identification using soft biometrics,”to be submitted.Conference PapersA. Dantcheva, J.-L. Dugelay, and P. Elia, “Person recognition using a bag of facial soft biometrics(BoFSB),”in Proc. of IEEE MMSP, 2010.A. Dantcheva and J.-L. Dugelay and P. Elia, “Soft biometric systems: reliability and asymptoticbounds,” in Proc. of BTAS, 2010.A. Dantcheva and N. Erdogmus and J.-L. Dugelay, “On the reliability of eye color as a softbiometric trait,” in Proc. of WACV, 2011.A. Dantcheva and J.-L. Dugelay, “Female facial aesthetics based on soft biometrics and photoquality,”in Proc. of ICME, 2011.A. Dantcheva and J.-L. Dugelay, “Frontal-to-side face re–identification based on hair, skin andcloths patches,” in Proc. of AVSS, 2011.A. Dantcheva, A. Singh, P. Elia, J. L. Dugelay, “Search pruning video surveillance systems:Efficiency-reliability tradeoff,” in Proc. of ICCV Workshop IWITINCVPR, 1st IEEE Workshopon Information Theory in Computer Vision and Pattern Recognition in the InternationalConference on Computer Vision, 2011.A. Dantcheva, P. Elia and J. -L. Dugelay, “Gain, reliability and complexity measures in biometricsearch pruning based on soft biometric categorization,” submitted to ICME 2011.A. Dantcheva, J. -L. Dugelay, “User Acceptance of Access Control based on Fingerprint, PIN,Soft Biometrics and Face Recognition,” submitted to ICB 2011.
16 1. PUBLICATIONSM. Ouaret, A. Dantcheva, R. Min, L. Daniel, J. -L. Dugelay, “BIOFACE, a biometric facedemonstrator,” ACMMM 2010, ACM Multimedia 2010, October 25-29, 2010, Firenze, Italy, pp 1613-1616.Book ChapterC. Velardo, J. -L. Dugelay, L. Daniel, A. Dantcheva, N. Erdogmus, N. Kose, R. Min, X. Zhao,“Introduction to biometry Book chapter of "Multimedia Image and Video Processing"” (2ndedition); CRC Press; 2011
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FACIAL SOFT BIOMETRICSMETHODS, APPL
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AcknowledgementsThis thesis would n
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6hair, skin and clothes. The propos
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97 Practical implementation of soft
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11Notations used in this workE : st
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13Chapter 1IntroductionTraditional
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15event of collision, which is of s
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17ric. In Section 6.6 we employ the
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19Chapter 2Soft biometrics: charact
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21is the fusion of soft biometrics
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23plied on low resolution grey scal
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25Chapter 3Bag of facial soft biome
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27In this setting we clearly assign
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29Table 3.1: SBSs with symmetric tr
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31corresponding to p(n,ρ). Towards
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the same category (all subjects in
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3.5.2 Analysis of interference patt
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an SBS by increasing ρ, then what
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39Table 3.4: Example for a heuristi
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41for a given randomly chosen authe
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43Chapter 4Search pruning in video
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45Figure 4.1: System overview.SBS m
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472.52rate of decay of P(τ)1.510.5
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49to be the probability that the al
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51The following lemma describes the
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534.5.1 Typical behavior: average g
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55n = 50 subjects, out of which we
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5710.950.9pruning Gain r(vt)0.850.8
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59for one person, for trait t, t =
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61Chapter 5Frontal-to-side person r
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63Figure 5.1: Frontal / gallery and
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6510.90.80.7Skin colorHair colorShi
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6710.90.80.70.6Perr0.50.40.30.20.10
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69Chapter 6Soft biometrics for quan
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71raphy considerations include [BSS
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73Figure 6.3: Example image of the
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75A direct way to find a relationsh
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77- Pearson’s correlation coeffic
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79shown to have a high impact on ou
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81Chapter 7Practical implementation
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834) Eye glasses detection: Towards
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857.2 Eye color as a soft biometric
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87Table 7.5: GMM eye color results
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89and office lights, daylight, flas
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917.5 SummaryThis chapter presented
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93Chapter 8User acceptance study re
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95Table 8.1: User experience on acc
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97scared of their PIN being spying.
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99Table 8.2: Comparison of existing
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101ConclusionsThis dissertation exp
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103Future WorkIt is becoming appare
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105Appendix AAppendix for Section 3
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107- We are now left withN −F = 2
Page 111 and 112: 109Appendix BAppendix to Section 4B
Page 113 and 114: 111Blue Green Brown BlackBlue 0.75
Page 115 and 116: 113Appendix CAppendix for Section 6
Page 117 and 118: 115Appendix DPublicationsThe featur
Page 119 and 120: 117Bibliography[AAR04] S. Agarwal,
Page 121 and 122: 119[FCB08] L. Franssen, J. E. Coppe
Page 123 and 124: 121[Ley96] M. Leyton. The architect
Page 125 and 126: 123[RN11] D. Reid and M. Nixon. Usi
Page 127 and 128: 125[ZG09] X. Zhang and Y. Gao. Face
Page 129: 2Rapporteurs:Prof. Dr. Abdenour HAD
Page 132 and 133: Biométrie faciale douce 2Les terme
Page 134 and 135: Biométrie faciale douce 4une perso
Page 136 and 137: Couleur depeauCouleur descheveuxCou
Page 138 and 139: Biométrie faciale douce 8Nous nous
Page 140 and 141: Biométrie faciale douce 103. Proba
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Page 144 and 145: Biométrie faciale douce 14Figure 6
Page 146 and 147: Biométrie faciale douce 16pages 77
Page 148 and 149: Reviewers:Prof. Dr. Abdenour HADID,
Page 150 and 151: 3hair, skin and clothes. The propos
Page 152 and 153: person in the red shirt”. Further
Page 154 and 155: 7- Not requiring the individual’s
Page 156 and 157: 9Probability of Collision10.90.80.7
Page 158 and 159: 11the color FERET dataset [Fer11] w
Page 160 and 161: 13Table 2: Table of Facial soft bio
Page 164 and 165: 17Bibliography[ACPR10] D. Adjeroh,
Page 166 and 167: 19[ZESH04] R. Zewail, A. Elsafi, M.
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