Lizzie Chapman Shelley Payne ITE 119.40 21 February 2016 Facial Recognition Technology in Gameplay Gamers have come a long way since the Atari days of the 1980’s. Atari’s simple beginnings have led to more complicated and intricate social gaming systems played by millions today. The gaming genre is quirky, creative and full of innovative designs. Gamers are always looking for new ways to enhance their experience. Realistic graphics and wireless controllers have certainly taken gaming to another level but the biggest enhancement for gamers has to be facial recognition. This technology allows the gamer to create avatars in their own likeness and actually be “in” the game. In order to create a “life-like” avatar, facial recognition technology …show more content…
“The first is the most benign: It’s called face detection, and it’s the software in phone cameras that says, “Hey, here’s a face,” then (often) auto-focuses the lens on it. The second is facial characterization, which discerns the demographics of a face: It sees not a generic human but a white male in his early thirties. (It’s this type of software that powers “smart billboards,” like the German video screen that only shows a beer ad when women walk by.)” (Meyer) Gaming facial and gesture recognition should really be called facial and body characterizations. This technology is so highly developed, that a person can be depicted by his/her gait, body type or hairstyle. All of these defined characteristics that are captured lead to the creation of a more realistic …show more content…
He is regarded as innovator for his work in artificial intelligence. Bledsoe’s work with pattern recognition as well as automated theorem proving, lead to what we know today as facial recognition. Much of his research was funded by an unspecified intelligence agency and publicity about his work was kept very quiet. He was given a book of mug shots and asked to create a data set that would pull images from a large database into a smaller record. He described some of the difficulties he encountered: “The recognition problem is made difficult by the great variability in head rotation and tilt, lighting intensity and angle, facial expression, aging, etc. Some other attempts at facial recognition by machine have allowed for little or no variability in these quantities. Yet the method of correlation (or pattern matching) of unprocessed optical data, which is often used by some researchers, is certain to fail in cases where the variability is great. In particular, the correlation is very low be-tween two pictures of the same person with two different head rotations.”