Transcript Soft Biometrics

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…
Beginning of soft
biometrics
19世纪
The term “soft biometrics” is introduced
2004
New definition of
soft biometric
2010
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.
Beginning of soft
biometrics
19世纪
The term “soft biometrics” is introduced
2004
New definition of
soft biometric
2010
Definition
• A.K.Jain et al. introduced the term “soft
biometric”[2]
– Not expensive to compute, can be sensed at a distance, donot require the cooperation of the surveillance subjects and have the aim to narrow down
the search from a group of candidate individuals.
Beginning of soft
biometrics
19世纪
The term “soft biometrics” is introduced
2004
New definition of
soft biometric
2010
Definition
• A.Dantcheva et al. gave new definition of soft
biometric.[3]
– Soft biometric traits are physical, behavioral or
adhered human characteristics, classifiable in predefined human compliant categories.
Beginning of soft
biometrics
19世纪
The term “soft biometrics” is introduced
2004
New definition of
soft biometric
2010
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
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
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
Case Study
Case Study
Case Study
Case Study
Case Study
References
• [1] H.T.F. Rhodes. Alphonse Bertillon: Father of scientific detection. Pattern
Recognition Letters, 1956.
• [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,
2004.
• [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, 2011. 2
• [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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