Faceprints As Symbology :: Symblogogy

Who needs a number when you have a face? That’s what we say here at Symblogogy!

Symbologies such as barcodes are rapidly being replaced by other pattern identifiers found through digital conversion.

As noted here a few months ago, ColorCode/ColorZip created a new type of symbology to be used for advertisers that takes a picture of an Ad an and converts it to a type of QR Code based symbology. The purpose here would allow the user access to additional information by taking a photograph with ones phone on the product Ad and digital image converted.

Here in Houston, they have created a different approach to digital conversion and identification. A webcam captures a continuous video stream which is used to detect the face of an individual and converts the images captured to a unique identifier … just like a barcode on a keyfob.

It will only be a matter of time when one can step up in line at the supermarket and have ones loyalty points automatically accrue and discounts awarded through photographic digital conversion as symbology access to database information capture and update.

This from NetworkWorld -

Forget your PIN? Use your face

Submitted by Layer 8 on Wed, 08/01/2007 - 11:49am.

Face recognition as a unique biometric is growing slowly in certain corporate and consumer applications, but researchers at the University of Houston (UH) are trying to make the technology far more ubiquitous and secure: they want it to replace the dozens of personal identification numbers (PIN), passwords and credit card numbers everyone uses every day.

The UH designed and built a prototype field-deployable 3D face recognition system that consists of a 3dMDTM optical scanner using a 1-pod configuration, which is connected to a PC.

----

When the subject is facing the camera and remains relatively still for more than two seconds, the system triggers the optical scanner and the 3D data of the individual's face are captured. The system can either enroll the subject into the database, or perform a scenario-specific task. In an identification scenario, the system will display the closest 5 datasets to the operator. In a verification scenario, the system will determine whether the subject is who they claim to be, based on a preset distance threshold, UH says.

The system determines not only the characteristics of each face, but also whether the person is wearing glasses, allowing for a practical system which offers high accuracy. So far, face recognition methods have focused on appearance - capturing, representing, and matching facial characteristics as they appear on two-dimensional images in the visible spectrum. This is quite challenging to machine recognition because such characteristics vary with orientation, age, habits (beard etc)), and illumination. Instead, the UH system uses three-dimensional information.

The system was highly rated by The National Institute of Standards and Technology (NIST) in its annual Face Recognition Vendor Test (FRVT) 2006 and the Iris Challenge Evaluation (ICE) 2006. NIST said the FRVT looks at face recognition from high-resolution still images and three-dimensional (3D) face images, and measures performance for still images taken under controlled and uncontrolled illumination. Face and iris are two biometrics that have been developed over the last 20 years. Face recognition is a vibrant area of biometrics with active research and commercial efforts.

----

"Remembering dozens of personal identification numbers and passwords is not the solution to identity theft. PINs and passwords are not only inconvenient to memorize, but also are impractical to safeguard. In essence, they merely tie two pieces of information together; once the secret is compromised, the rest follows. The solution is to be able to tie your private information to your person in a way that cannot be compromised," said Eckhard Pfeiffer Professor of Computer Science and director of the UH Computational Biomedicine Laboratory.

----

NIST last year released the Multimodal Biometric Application Resource Kit (MBARK), an open source middleware package that enables you to plug in biometric sensors from different manufacturers. The kit also contains templates and sample apps. All the details and the software can be downloaded from the NIST Web site.