Advances in Pattern Recognition Technologies

By Thomas Liu

Pattern recognition technologies have been with us throughout the digital revolution. Until recently, it was a privilege only used by governments and large corporations. However, as processing power becomes cheaper, and “smart” devices become more widely used, the market for recognition technologies increased too.
Remember the embarrassing video of Steve Jobs making typos on his own iPad presentation? IBM’s developed a program that over a period of time gathers finger skin touch area, finger size and finger position for the logged in user. Using this information, the virtual key buttons are automatically resized, reshaped and repositioned in response. To read more, click here.

Along with IBM’s pattern recognition touchscreen program, academics from numerous US universities are testing a new micro-vibration system, which when implemented on a touchscreen will trick the nerves to believe the screen is hollowed with indents. This is especially effective for cramped screens as it helps guide people to accurately click where they want.  To read more, click here.

The last technology is not so new, but its applications are. For quite some time, facial recognition had been used only by the government. Two key elements, both of which the government has access too, are required: software that analyzes images and databases of identifying information that can link faces to names. Can’t do much with one without the other. Recently however, the online behemoth, Facebook, is rolling out facial-recognition technology that will automatically suggest names of friends in photos that are being uploaded. Google too has the data for facial tracking, and they’ve developed a tracking program.  Originally, it was planned so Google Goggles (a mobile app) would allow the user to take a picture of someone’s face and Google will match it with other related information. It was not released due to privacy concerns. To read more, click here.

As digital technologies advance, pattern recognition will no doubt become more accurate. These technologies are normally helpful to people, but it could be abused. It is up to us to monitor its direction.

Thomas Liuis an undergrad student at the University of Toronto, Mississauga.  He is currently enrolled in the Commerce program pursuing a specialist in Accounting and Finance.  Thomas is a summer intern with the Altitude Accelerator acting as Research Associate / Market Analyst.

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