Alex Hauptmann, a professor at Carnegie Mellon who specializes in this sort of computer analysis, says that although AI has propelled the field forward hugely in recent years, there are still fundamental challenges in getting computers to understand video. And the biggest of these is a challenge for cameras we don’t often think about anymore: resolution. Take, for example, a neural network that’s been trained to analyze human actions in a video. These work by breaking down the human body into segments — arms, legs, shoulders, heads, etc. — then watching how these stick figures change from one frame of video to the next. From this, the AI can tell you whether someone’s running, for example, or brushing their hair. “But this depends on the resolution of the video you have,” Hauptmann tells The Verge. “If I’m looking at the end of a parking lot with one camera, I’m lucky if I can tell if someone opened a car door. If you’re right in front of a [camera] and playing a guitar, it can track you down to the individual fingers.”
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