be in your face JUNE 26 2011 Page 11 So if you’re smart, act now. This special introductory rate is available for a limited time only. To pay less and own your own home sooner, call 13 29 30, visit qtcu.com.au or your local branch. QTCU’s Intro Rate Home Loan offer now just 6.87%p.a. (7.63%p.a. Comparison Rate) * NOW THAT’S CLEVER THINKING. Lending criteria, terms, conditions, fees and charges apply. *Discount available on new borrowings and not in conjunction with any other offers or discounts and is for first 12 months after loan funded, then rate reverts to Variable Rate. Product is Mortgage Breaker Home Loan. Rates current at 20 June 2011 and subject to change. Comparison rate calculated on loan amount of $150,000 for a term of 25 years based on monthly repayments. WARNING: This comparison rate is true only for the example given and may not include all fees and charges. Different terms, fees or other loan amounts might result in a different comparison rate. ACL 241195. # Saving based on $350,000 home loan. POINTS OF RECOGNITION Searches for shadows and wrinkles to help determine age. Software reads shape of lips to determine mood and gender. Eyebrow shape key to determining mood of person. Jewellery can help software determine gender. Shadows cast by hair used to determine gender. WHAT FACIAL RECOGNITION FOUND Gender: Female Age: Young Adult Angry: 0 Happy: About 85 per cent Sad: 0 Surprised: 0 Facial recognition software uses an algorithm, or mathematical process, to produce a “face print’’ that can be matched against a database or used to collect statistics, such as by a retailer wanting to know the demographic of its shoppers. More than 20 nodal points, based on facial features, are selected. The distance between nodal points is then measured to produce a matrix of numbers. More than 400 metrics are used to interpret gender, age and mood. WHAT THE TECHNOLOGY WILL BE USED FOR Facial recognition is already in use at major airports and there are plans for it to be used for public surveillance to reduce crime and to improve border security. Queensland’s new smart licences are equipped with facial recognition. The technology is also being used to improve customer service in the retail sector. Future uses could see it used instead or as well as a PIN number at ATMs to reduce fraud. Computer software can assess the overall texture of skin to help determine age. Can also detect moles and other features. Cameras will follow our every mood Kelmeny Fraser Consumer affairs Face facts: John Anderson. Picture: Mark Cranitch A GROUP of teenage girls enter a shop. As they pass through the doors, a camera is activated. Their images are not re- corded, but facial recognition software linked to the shop’s camera fires up, spitting out a stream of interpretive data. The girl on the left with the braces is recorded as female, young and slightly sad. The smiling girl beside her rates high on the happy chart. As the group moves around the shop, the readings are used to change the digital in- store advertising to target the shoppers. And the retailer at the end of the week has a concise set of demographic data of its shoppers, with an accuracy rate of higher than 85 per cent. Sound like a vision for shopping in the future? It’s already in use and could soon come to a store near you. The brainchild behind the facial recognition software is Brisbane-based firm Yeah- point, which has already at- tracted the attention of lead- ing top-five technology com- pany Toshiba, which this year bought a 12 per cent stake. Yeahpoint CEO John Anderson said the improved reliability of facial recognition technology had opened up possibilities in retail. ‘‘It is now coming of age and a cost where it is becom- ing commercially viable,’’ Mr Anderson said. One Yeahpoint application being trialled in New South Wales can interpret the mood of shoppers as they move about a store. Mathematical formulas based on the distance be- tween and shape of facial features are used to collect valuable data, giving infor- mation about a shopper’s gender, mood and age. Another application about to be rolled out in clothing outlets across the country can be used to help shoppers choose outfits. The MiMirror terminal en- ables shoppers to try a series of outfits, save pictures of each and share them with friends via Facebook for feedback. When the MiMirror session expires, usually after 15 minutes, the images are erased from the system. Facial recognition could also help shoppers avoid the deli counter queue by using a touch-screen to make an or- der, which is then linked to a photograph of their face. Another camera at the checkout scans faces to match orders so they’re delivered before it’s time to pay. Crooks target rich for scams Kay Dibben Crime FOREIGN criminals have been caught with ‘‘target lists’’ of Queensland scam victims, compiled from marketing in- formation bought from Aust- ralian companies. Queensland fraud detec- tives are tracking down the multiple victims of a cell of Nigerian fraudsters who re- cently were arrested in Spain. The Nigerian crooks were found with target lists, includ- ing extensive details of Aust- ralians, purchased from database companies. Superintendent Brian Hay of Queensland’s Fraud and Corporate Crime Group said the crooks in some cases posed as lawyers buying marketing lists ‘‘for charitable reasons’’. ‘‘Some of the lists I saw had people’s age, earning potential, occupation, addresses, email addresses and phone num- bers,’’ he said. Supt Hay said that in one case lists of Australians over the age of 50, with investment portfolios worth more than $250,000, were wanted. In another case lists of senior mining industry executives were sought. ‘‘If they have information about a person’s occupation, age, earning capacity, invest- ment portfolio and demo- graphics, they can then see if the person is in a good or bad area by doing a Google search. ‘‘They then can go to Facebook and LinkedIn and prepare a dossier and develop a story they know will appeal to a person and send them an email or letter or phone them to scam money.’’ Queensland University of Technology senior lecturer in business Dr Larry Neale said there was a huge business in selling marketing lists, created from personal information provided when people filled in lifestyle surveys, entered com- petitions or bought products. thesundaymail.com.au 11 NEWS thesundaymail.com.au SPECIAL INVESTIGATION