Soft Biometrics 苏毅婧

Outline Introduction Application Case study

Outline Introduction – Motivation – Definition – Characteristics Application Case study

Why use soft biometrics Biometric systems – Unimodal biometric system Noise Non-universality Impostor Error rate… – Multimodal biometric system Cost Longer verification time – Use soft biometrics as ancillary information

Outline Introduction – Motivation – Definition – Characteristics Application Case study

Definition Biometric characteristic should satisfies: – Universality: each person should have the characteristic. – Distinctiveness: any two persons should be sufficiently different in terms of the characteristic. – Permanence: the characteristic should be sufficiently invariant (with respect to the matching criterion) over a period of time. – Collectability: the characteristic can be measured quantitatively.

Definition Alphonse Bertillon firstly introduced the idea for a personal identification system based on biometric. [1] – Colors of eye, hair, beard and skin; – Shape and size of the head… 19 世纪 Beginning of soft biometrics The term “soft biome- trics” is introduced New definition of soft biometric

Definition A.K.Jain et al. introduced the term “soft biometric” [2] – Soft biometrics provide some information about the individual, but lack of distinctiveness and permanence to sufficiently differentiate any two individuals. 19 世纪 Beginning of soft biometrics The term “soft biome- trics” is introduced New definition of soft biometric

Definition A.K.Jain et al. introduced the term “soft biometric” [2] – Not expensive to compute, can be sensed at a dis- tance, donot require the cooperation of the surve- illance subjects and have the aim to narrow down the search from a group of candidate individuals. 19 世纪 Beginning of soft biometrics The term “soft biome- trics” is introduced New definition of soft biometric

Definition A.Dantcheva et al. gave new definition of soft biometric. [3] – Soft biometric traits are physical, behavioral or adhered human characteristics, classifiable in pre- defined human compliant categories. 19 世纪 Beginning of soft biometrics The term “soft biome- trics” is introduced New definition of soft biometric

Soft biometric traits

Outline Introduction – Motivation – Definition – Characteristics Application Case study

Characteristics(advantages) Human compliant – Traits are conform with natural human description labels. Computational efficient – Sensor and computational requirements are marginal. Enrolment free – Training of the system is performed off-line and without prior Knowledge of the inspected individuals. Deducible from classical biometrics – Traits can be partly derived from images captured for primary biometric identifier

Characteristics(advantages) Non intrusive – Data acquisition is user friendly or can be fully imperceptible. Identifiable from a distance – Data acquisition is achievable at long range. Not requiring the individual’s cooperation – Consent and contribution from the subject are not needed. Preserving human privacy – The stored signatures are visually available to everyone and serve in this sense privacy.

Characteristics(limitations) Lack of distinctiveness and permanence Method to overcome the limitation – Fused soft biometric traits

Outline Introduction Application – Fusion with classical biometric trait – Pruning the search – Human identification Case study

Fusion with classical biometric trait

n users enrolled in the database X the primary biometric system feature vector soft biometric feature vector Bayes rule:

Fusion with classical biometric trait Fingerprint + gender, ethnicity, height [4] – Improvement of 5% Fingerprint + weight, some weight measures [5] Error rate 3.9% => 1.5%

Outline Introduction Application – Fusion with classical biometric trait – Pruning the search – Human identification Case study

Pruning the search

n users enrolled in the database X the primary biometric system feature vector soft biometric feature vector Target : – Filter W and to find a subset of the dataset Z

Outline Introduction Application – Fusion with classical biometric trait – Pruning the search – Human identification Case study

Human identification

Case Study Soft-biometrics: Unconstrained Authentication in a Surveillance Environment – Simon Denman, Clinton Fookes, Alina Bialkowski, Sridha Sridharan

Case Study

References [1] H.T.F. Rhodes. Alphonse Bertillon: Father of scientific detection. Pattern Recognition Letters, [2] A.K. Jain, S.C. Dass, and K. Nandakumar. Soft biometric traits for personal recognition systems. In Proceedings of ICBA, pages 1–40. Springer, [3] A. Dantcheva, C. Velardo, A. DAngelo, and J.-L. Dugelay. Bag ofsoft biometrics for person identification: New trends and challenges. Multimedia Tools and Applications, 51(2):739–777, [4].K.Jain,S.C.Dass,andK.Nandakumar.Softbiometrictraitsforpersonalrecog nition systems.In ProceedingsofICBA,pages1–40.Springer,2004. [5].Ailisto,E.Vildjiounaite,M.Lindholm,S.M.Makela,andJ.Peltola.Softbiomet rics–combiningbodyweightandfatmeasurementswithfingerprintbiometrics. PatternRecog-nitionLetters,27(5):325–334,2006

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