facial recognition in biometrics

Susan SimmonsSusan Simmons

University of North Carolina University of North Carolina WilmingtonWilmington

Facial Recognition in Facial Recognition in BiometricsBiometrics

BiometricsBiometrics Biometrics (wikipedia) -- Biometrics are used to identify the identity of an input Biometrics (wikipedia) -- Biometrics are used to identify the identity of an input

sample when compared to a template, used in cases to identify specific people sample when compared to a template, used in cases to identify specific people by certain characteristics.by certain characteristics. possession-based: using one specific "token" such as a security tag or a cardpossession-based: using one specific "token" such as a security tag or a card knowledge-based: the use of a code or password. knowledge-based: the use of a code or password. Biometric – physical or behavioral characteristicBiometric – physical or behavioral characteristic

Biometrics (questbiometric.com) -- The word "biometrics" is derived from the Biometrics (questbiometric.com) -- The word "biometrics" is derived from the Greek words 'bios' and 'metric' ; which means life and measurement respectively. Greek words 'bios' and 'metric' ; which means life and measurement respectively. This directly translates into "life measurement”. General science has included This directly translates into "life measurement”. General science has included biometrics as a field of statistical development since the early twentieth century. biometrics as a field of statistical development since the early twentieth century.

Biometrics technologies measure a particular set of a person's vital statistics in Biometrics technologies measure a particular set of a person's vital statistics in order to determine identityorder to determine identity. .

Biometrics in the high technology sector refers to a particular class of Biometrics in the high technology sector refers to a particular class of identification technologies. These technologies use an individual's unique identification technologies. These technologies use an individual's unique biological traits to determine one's identity or to verify one’s identity.biological traits to determine one's identity or to verify one’s identity.The The traits that are considered include fingerprints, retina and iris patterns, facial traits that are considered include fingerprints, retina and iris patterns, facial characteristics and many more.characteristics and many more.

A little historyA little history

ExamplesExamples

We see biometrics in many We see biometrics in many different places today.different places today.

Voter Registration Voter Registration Driver Licensing Driver Licensing Border Control Border Control Passport / VISA Passport / VISA Criminal ID / Wanted Persons Lookup Criminal ID / Wanted Persons Lookup Airports / Frequent Traveler / Passenger Airports / Frequent Traveler / Passenger

TrackingTracking

Facial recognitionFacial recognition Can be used for surveillanceCan be used for surveillance

Find criminals, terrorists, missing childrenFind criminals, terrorists, missing children Involves non-invasive, contact-free processInvolves non-invasive, contact-free processCan be integrated with existing surveillance Can be integrated with existing surveillance

systemssystems MarketingMarketing

Identify demographics interested in productsIdentify demographics interested in products Some examplesSome examples

http://www.youtube.com/watch?v=H2a0KYtG97Ehttp://www.youtube.com/watch?v=H2a0KYtG97E http://www.youtube.com/swf/l.swf?video_id=jADItDHOHOAhttp://www.youtube.com/swf/l.swf?video_id=jADItDHOHOA

Problems in Facial recognitionProblems in Facial recognition Privacy issues facial recognitionPrivacy issues facial recognition

Violation of people’s privacy?Violation of people’s privacy?Right to search database for match of images Right to search database for match of images

captured in public surveillance cameras?captured in public surveillance cameras? Uncontrolled background (including lighting, Uncontrolled background (including lighting,

shadows, glares)shadows, glares) Camera angleCamera angle Image resolutionImage resolution Part of face hidden (sunglasses, hat, profile, etc)Part of face hidden (sunglasses, hat, profile, etc)

Identify facial images Identify facial images Need to identify facial images from a video or pictureNeed to identify facial images from a video or picture

EigenfacesEigenfaces Take an Take an NN x x NN image and convert it to an image and convert it to an NN22 x 1 vector x 1 vector Use a subset of the face images as a training set (each face Use a subset of the face images as a training set (each face

must be centered and of the same size)must be centered and of the same size) Calculate the eigenvectors of the covariance matrix of the Calculate the eigenvectors of the covariance matrix of the

images, keeping on images, keeping on K K eigenvectors (corresponding to the eigenvectors (corresponding to the larges larges KK eigenvalues) eigenvalues)

Uses of eigenfacesUses of eigenfaces After centering new images, calculate the distance between After centering new images, calculate the distance between

the new image and all images in database. If distance is the new image and all images in database. If distance is less than a set cutoff, then the picture is recognized as that less than a set cutoff, then the picture is recognized as that face.face.

Can also do this same exercise to determine if an image is a Can also do this same exercise to determine if an image is a face.face.

Active Appearance ModelsActive Appearance Models The following approach works well with facial The following approach works well with facial

images that are forwarding facing and not images that are forwarding facing and not much facial expression.much facial expression.

The shape of a face is found using Active The shape of a face is found using Active Shape Models (ASM). Identifies the outline Shape Models (ASM). Identifies the outline of the face as well as important landmarks on of the face as well as important landmarks on the face.the face.

Sean Connery (1959)Sean Connery (1959)

Modeling shape in AAMsModeling shape in AAMs The algorithm uses a subset of images to The algorithm uses a subset of images to

train the model.train the model. Points are aligned into a common co-ordinate Points are aligned into a common co-ordinate

frame and represented by a vector frame and represented by a vector xx ( (xx = ( = (xx11, ,

xx22,,xx33…, …, yy11, , yy22, , yy33,…),…)TT).). Principal Component Analysis (PCA) is then Principal Component Analysis (PCA) is then

applied to the dataapplied to the data

ssbPxx

Modeling grey-level appearanceModeling grey-level appearance Each image is warped so that its control Each image is warped so that its control

points match the mean shape (using a points match the mean shape (using a triangulation algorithm)triangulation algorithm)

To minimize the effect of global lighting To minimize the effect of global lighting variation, we normalize the example samples variation, we normalize the example samples by applying scaling and offsetby applying scaling and offset

PCA is applied to the normalized dataPCA is applied to the normalized data /)( 1gg im

ggbPgg

Using the models to vary Using the models to vary parametersparameters

MovieMovie

Varying the first parameter Varying the seventh parameter

Age estimationAge estimation

Random Forest (by Leo Brieman) uses Random Forest (by Leo Brieman) uses decision trees to estimate age. decision trees to estimate age.

Support Vector Regression – (input info about Support Vector Regression – (input info about support vector regression)support vector regression)

MAEMAE % error w/% error w/+55

Random ForestRandom Forest 12.0471312.04713 0.17222220.1722222

Support Vector MachineSupport Vector Machine 9.254012 9.254012 0.35555560.3555556

Aging facesAging faces

Current methodologyCurrent methodology

Use Monte Carlo simulation to simulate potential Use Monte Carlo simulation to simulate potential b vectorsb vectors

Use a classification method from the model to Use a classification method from the model to estimate age (for example, support vector estimate age (for example, support vector regression or random forest, etc)regression or random forest, etc)

Create a look-up table for the average b-vectorsCreate a look-up table for the average b-vectors Use the look-up values to age individuals (use Use the look-up values to age individuals (use

their b-vectors)their b-vectors)

An exampleAn exampleA hypothetical “b-vector look-up table with the dimension of b = 4A hypothetical “b-vector look-up table with the dimension of b = 4

AGEAGE2.130630 2.130630 6.953627 6.953627 -1.232983 -1.232983 2.723359 202.723359 20-0.9059754 -0.9059754 0.5859145 0.5859145 -4.1489520 -4.1489520 0.5211284 250.5211284 25 5.6084822 5.6084822 -0.3766133 -0.3766133 3.4587549 3.4587549 9.8395541 309.8395541 30

A new individual’s “b-vector” at age 20A new individual’s “b-vector” at age 201.6752062 1.6752062 0.2979551 0.2979551 3.8977920 3.8977920 5.17418535.1741853

To age this individual to 30, we need to shift their b-valuesTo age this individual to 30, we need to shift their b-values1.6752062 + (5.6084822 - 2.130630) = 5.1530581.6752062 + (5.6084822 - 2.130630) = 5.153058

0.2979551 + (-0.3766133 - 6.953627) = -7.0322850.2979551 + (-0.3766133 - 6.953627) = -7.0322853.8977920 +(3.4587549 – (-1.232983 )) = 8.589533.8977920 +(3.4587549 – (-1.232983 )) = 8.589535.1741853 + (9.8395541 - 2.723359) = 12.290385.1741853 + (9.8395541 - 2.723359) = 12.29038

Some examplesSome examples

ConclusionsConclusions

Biometrics continuously receives Biometrics continuously receives more attentionmore attention

Need to create databaseNeed to create databaseMuch more work to be done by Much more work to be done by

MANY different fieldsMANY different fields

Special Thanks toSpecial Thanks to

Ms. Amrutha SethuramMs. Amrutha SethuramDrs. Karl Ricanek (Computer Science), Drs. Karl Ricanek (Computer Science),

Yishi Wang (Statistics)Yishi Wang (Statistics)Mr. Fernando Schiefelbein (graduate Mr. Fernando Schiefelbein (graduate

student), Mr. Philip Whisenhurst student), Mr. Philip Whisenhurst (undergraduate student)(undergraduate student)