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Facial recognition



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  • -Age is an issue: a study by government’s National Insitute of Standards and Technology found false negative rates for face-recognition verification of 43 percent using photos from only 18 months earlier
  • Skin biometrics: surface texture analysis of texture of skin, uses algorithms to turn patch of skin into mathematical, measurable space Can define the differences between twins Many problems wouldn’t work if: significant glare on sunglasses, long hair in center of face, poor lighting, lack of resolution
  • detection: scans already existing 2d photograph or a shot from a 3D video Alignment: up to 90 degrees turned hereMeasurement: measures curves of face on submillimeter scale and creates a templateRepresentation: translates into unique code to create template with set of numbers to represent a person’s faceMatching: new technology converts 3D image into 2D image using algorithm to compare to 2D image in database
  • From :55 to 2:05ish


  • 1. Christina Carr, Becky Schaffran, & Tess CiminiFACIAL RECOGNITION
  • 2. What is it? Facial recognition systems are built on computer programs that analyze images of human faces for the purpose of identifying them.
  • 3. How does it work? Measure specific facial characteristics to create unique file called “template” Using templates, compare image to another image  Produces a score on similarity  Video camera signals  Pre-existing photos  i.e. drivers license databases
  • 4. 2D Facial Recognition 2D Recognition  Maximum angle: 35 degrees  Must be similar to program in database  Sometimes ineffective due to lighting changes and other uncontrolled variables
  • 5. 3D Recognition 3D Recognition  Can create template from face at 90 degree angle  More accurate  Uses depth and an axis of measurement not affected by lighting Example: Identix® - FaceIt®  Landmarks or nodal points  And now: FaceIt®Argus, skin biometrics
  • 6. Steps of 3D Recognition
  • 7. Uses • Law Enforcement Security • Casinos, Super Bowl, Olympics • Border controlTransportation • E-passports • FacebookEntertainment • SceneTap
  • 8. Security Closed-circuit television (CCTV)  Surveillance technology crosschecked with mugshot databases
  • 9. Security Casinos Super Bowl  Tampa, Fl. (2001): 19 people identified London 2012 Olympics MORIS
  • 10. Transportation Germany: Fully automated border controls Australia: SmartGate  Compares the face of the individual with image in the e-passport microchip
  • 11. Entertainment  Facebook Tag Suggest  SceneTap  50 Chicago bars  Apps in progress  Apple
  • 12. New Developments ATM’s Advertising & marketing “Adidas is working with Intel to install and test digital walls with facial recognition in a handful of stores either in the U.S. or Britain. If a woman in her 50s walks by and stops, 60% of the shoes displayed will be for females in her age bracket, while the other 40% will be a random sprinkling of other goods. ‘If a retailer can offer the right products quickly, people are more likely to buy something,’ said Chris Aubrey, vice president of global retail marketing for Adidas.”
  • 13. “Facial Recognition TechnologyChallenges Privacy” http://abclocal.go.com/kgo/video?id=842585 5&syndicate=syndicate&section
  • 14. Limitations Not 100% accurate. Accuracy can fluctuate because of:  picture quality  Lighting  camera positions  facial expressions  and more
  • 15. Security Issues Mistaken identity cases Images cannot be used to convict suspects The CCTV cameras in London  1 crime solved per 1000 cameras
  • 16. CCTV Clip http://www.youtube.com/watch?v=fLEtzI1oe wI
  • 17. MORIS Mobile Offender Recognition and Information System Illegal search without a warrant No information is stored
  • 18. Facebook Has roughly 600 million users  that means that Facebook has a database of 600 million faces. Each time you “tag” a photo, Facebook learns more about your face.
  • 19. Google Picasa uses the same tagging techniques People fear a face recognition update to the app Google Goggles.  the app may even be able to identify peoples SSNs just from the photo.
  • 20. Adam Harvey•CV Dazzle•Foundways tocheat facerecognition