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‘Machine Vision’ Applied to Hockey
by Alanah McGinley on 10/06/08 at 03:14 PM ET
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From Shane Schick at itWorldCanada:
“When I was in graduate school (at Dartmouth College), I got hooked on hockey,” [Ryan Lilien] says. “When I came to the University of Toronto about two years ago, my focus was on computational biology, but this is Canada. I wanted to see if we could do something that could combine both interests.” The result is a project called the Computational Analysis of Ice Hockey Gameplay. The goal is to develop a system that will learn how hockey is played and help a team improve their performance. Or better yet, help a team like the Penguins understand how Osgood knew just where and how to move in those last 10 seconds, and how they could outthink him.
“Tracking the puck is hard. It’s small,” he says. “As a hockey fan, you don’t always see the puck, but you know based on the position of the players where the puck is and where they’re moving. The computer could do the same thing.”
Lilien’s approach is to use “machine vision,” a subfield of engineering that encompasses computer science, optics, mechanical engineering, and industrial automation.
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Tags: machine+vision, ryan+lilien, university+of+toronto,
