GVU Technical Report Number:
GIT-GVU-00-11
Title:
Machine Learning for Video-Based Rendering
Authors:
Arno Schoedl
Irfan Essa
Abstract:
We recently introduced a new paradigm for computer animation,
video textures, which allows us to use a recorded video to generate
novel animations by replaying the video samples in a new order.
Video sprites are a special type of video texture. Instead of storing
whole images, the object of interest is separated from the background
and the video samples are stored as a sequence of alpha-matted
sprites with associated velocity information. They can be rendered
anywhere on the screen to create a novel animation of the object.
To create such an animation, we have to find a sequence of sprite
samples that is both visually smooth and shows the desired motion.
In this paper, we address both problems. To estimate visual
smoothness, we train a linear classifier to estimate visual similarity
between video samples. If the motion path is known in advance,
we then use a beam search algorithm to find a good sample sequence.
We can also specify the motion interactively by precomputing a set of
cost functions using Q-learning.
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