Johannes Kopf     Michael Cohen     Richard Szeliski
Microsoft Research     Microsoft Research     Microsoft Research
       



We present a method for converting first-person videos, for example, captured with a helmet camera during activities such as rock climbing or bicycling, into hyper-lapse videos, i.e., time-lapse videos with a smoothly moving camera.

At high speed-up rates, simple frame sub-sampling coupled with existing video stabilization methods does not work, because the erratic camera shake present in first-person videos is amplified by the speed-up.


Scene Reconstruction
Our algorithm first reconstructs the 3D input camera path as well as dense, per-frame proxy geometries. We then optimize a novel camera path for the output video (shown in red) that is smooth and passes near the input cameras while ensuring that the virtual camera looks in directions that can be rendered well from the input.
Next, we compute geometric proxies for each input frame. These allow us to render the frames from the novel viewpoints on the optimized path.

Proxy Geometry

Stitched & Blended
Finally, we generate the novel smoothed, time-lapse video by rendering, stitching, and blending appropriately selected source frames for each output frame. We present a number of results for challenging videos that cannot be processed using traditional techniques.

We are working hard on making our Hyperlapse algorithm available as a Windows app.
Stay tuned!


Update: click here to read about the difference between Microsoft's and Instagram's hyperlapse algorithms.

Technical
paper

PDF (35.0 MB)
Supplemental
Material

Click here
High-res Video
Demo (148 MB)
Technical (287 MB)

This video provides a more technical explanation of our system: