Faces in the Crowd

Neural networks–by now a household term, at least in our IT house–are kind of ambidextrous.  They can use historical data to either predict or classify.  Sometimes both hands work together, and a neural network will make predictions based on classification.  One of the more interesting classification applications of this technology that made it into the press this week is software that analyzes the human traffic that makes its way through a particular room.  

The ‘intelligence audience measurement’ software can count people.  It can recognize and categorize gestures.  It can recognize people according to their gender or their generation.  Isafetek, the company that developed the software, calls its ability to count and classify people in a group “pattern recognition.”   According to the developer the platform has promise not only as operational risk software for public spaces such as airports but for advertising and marketing efforts, where statistical analysis of the data collected on a particular group of passersby in a particular place could be useful.

If this introduction brings up fears about Big Brother, don’t worry.   You won’t be an identifiable face in the crowd.  You won’t even be a face in the crowd.  You’ll be a type of face in a group in another group in a crowd.

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