Hyperlapse, Instagram’s New App, Turns Your Jittery Videos into Timelapse Movie-Magic
Today, Instagram is lifting the veil on Hyperlapse, one of the company’s first apps outside of Instagram itself. Using clever algorithm processing, the app makes it easy to use your phone to create tracking shots and fast, time-lapse videos that look as if they’re shot by Scorsese or Michael Mann. What was once only possible with a Steadicam or a $15,000 tracking rig is now possible on your iPhone, for free. (Instagram hopes to develop an Android version soon, but that will require changes to the camera and gyroscope APIs on Android phones.) And that’s all thanks to some clever engineering and an elegantly pared-down interaction design. The product team shared its story with WIRED.
By day, Thomas Dimson quietly works on Instagram’s data, trying to understand how people connect and spread content using the service. Like a lot of people working at the company, he’s also a photo and movie geek — and one of his longest-held affections has been for Baraka, an art-house ode to humanity that features epic tracking shots of peoples all across the world.
“It was my senior year, and my friend who was an architect said, ‘You have to see it, it will blow you away,’ ” Dimson says. He wasn’t entirely convinced. The movie, after all, was famous for lacking any narration or plot. But watching the film in his basement, Dimson was awestruck. “Ever since, it’s always been in the back of my mind,” he says.
A sample shot from Baraka.
By 2013, Dimson was at Instagram. That put him back in touch with Alex Karpenko, a friend from Stanford who had sold his startup to Instagram in 2013. Karpenko and his firm, Luma, had created the first-ever image-stabilization technology for smartphone videos. That was obviously useful to Instagram, and the company quickly deployed it to improve video capture within the app. But Dimson realized that it had far greater creative potential. Karpenko’s technology could be used to shoot videos akin to all those shots in Baraka. “It would have hurt me not to work on this,” says Dimson.
The insight that powered Karpenko’s algorithms began, like so many other startup ideas, as a Ph.D. thesis at Stanford. This was 2010, and the iPhone 4 had come out: one of the first phones that could capture HD video. That sounded terrific in theory, but cramming such a great video camera onto a handheld device meant that the videos themselves were often shaky to the point of being unwatchable. “They were all just crappy,” Karpenko says.
He knew that image stabilization was the answer, but the technologies of that time, which you’d find in Final Cut and myriad other video editing programs, were simply unworkable for smartphones. Why? Imagine a video clip taken from a moving car. To even the juddering camera motion, image stabilization algorithms typically analyze a movie frame by frame, identifying image fragments common to each. By recording how those shared points jump around across frames, the algorithms can then infer how the camera has been moving. By reverse-engineering that motion data, software can recreate a new, steadier version of a film clip. Yet every step in that process requires processing muscle. That’s fine for a movie studio, which has massive computers that crank overnight to re-render a scene. It’s ridiculous for a smartphone.