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., timelapse
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. 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 that passes near the input cameras while ensuring
that the virtual camera looks in directions that can be rendered
well from the input. Finally, we generate the novel smoothed, timelapse
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.