Space-Time Super-Resolution from a Single Video
Oded Shahar,
Alon Faktor,
Michal Irani
This webpage presents the paper "Space-Time Super-Resolution from a Single Video" (CVPR 2011).
Paper [PDF] [bibtex]
Abstract
Spatial Super Resolution (SR) aims to recover fine image details, smaller than a pixel size.
Temporal SR aims to recover rapid dynamic events that occur faster than the video frame-rate,
and are therefore invisible or seen incorrectly in the video sequence. Previous methods for
Space-Time SR combined information from {multiple} video recordings of the same dynamic scene.
In this paper we show how this can be done from a {single video recording}.
Our approach is based on the observation that small space-time patches (`ST-patches', e.g., 5x5x3)
of a single `natural video', recur many times inside the same video sequence at multiple spatio-temporal scales.
We statistically explore the degree of these ST-patch recurrences inside `natural videos',
and show that this is a very strong statistical phenomenon.
Space-time SR is obtained by combining information from multiple ST-patches at sub-frame accuracy.
We show how finding similar ST-patches can be done both efficiently (with a randomized-based search in space-time),
and at sub-frame accuracy (despite severe motion aliasing). Our approach is particularly useful for temporal SR,
resolving both severe motion aliasing and severe motion blur in complex `natural videos'.
Example Videos:
Fan Video:
Flag Video:
Treadmill Video:
Turbine Video:
Dirty Dancing Video:
