Apple introduced Live Photos feature in iPhone 6S which was rather useless for people who use Google Photos, as this was not supported by Google Photos but it was only until March. Google later extended its support for Live Photos format in order to retain iPhone users to use their app, as Apple has a major share in smartphone space.
There are a lot of apps out there in the market that converts Live Photos to GIFs, however, they lag something by themselves. Google has now launched a new app called the Motion Stills that does the same task as the other apps do, but it is something special. Eventually, it is far better than a basic Live Photos to GIF converter, developed within the Google’s research lab. The Motion Stills’ video stabilization algorithm converts your Live Photo to amazing GIFs even they are shaky. It’s a virtual camera for your Live Photos that actually freezes the background into a still photo or create sweeping cinematic pans. The resulting looping GIFs and movies come alive, and can easily be shared via messaging or on social media.
You can even make a storyboard telling your adventures by combining multiple clips into a movie montage. You don’t need neither an active data connection to work with this app nor a Google account to use it, everything is on-device.
How it actually works? Here’s how the blog post explains it:
We pioneered this technology by stabilizing hundreds of millions of videos and creating GIF animations from photo bursts. Our algorithm uses linear programming to compute a virtual camera path that is optimized to recast videos and bursts as if they were filmed using stabilization equipment, yielding a still background or creating cinematic pans to remove shakiness.
Our challenge was to take technology designed to run distributed in a data center and shrink it down to run even faster on your mobile phone. We achieved a 40x speedup by using techniques such as temporal subsampling, decoupling of motion parameters, and using Google Research’s custom linear solver, GLOP. We obtain further speedup and conserve storage by computing low-resolution warp textures to perform real-time GPU rendering, just like in a videogame.
Short videos are perfect for creating loops, so we added loop optimization to bring out the best in your captures. Our approach identifies optimal start and end points, and also discards blurry frames. As an added benefit, this fixes “pocket shots” (footage of the phone being put back into the pocket).
To keep the background steady while looping, Motion Stills has to separate the background from the rest of the scene. This is a difficult task when foreground elements occlude significant portions of the video, as in the example below. Our novel method classifies motion vectors into foreground (red) and background (green) in a temporally consistent manner. We use a cascade of motion models, moving our motion estimation from simple to more complex models and biasing our results along the way
Google’s Motion Stills is available on the App Store for free.