SimpleFlow: A Non-iterative, Sublinear Optical Flow Algorithm
Date
2012Author
Tao, Michael
Bai, Jiamin
Kohli, Pushmeet
Paris, Sylvain
Metadata
Show full item recordAbstract
Optical flow is a critical component of video editing applications, e.g. for tasks such as object tracking, segmentation, and selection. In this paper, we propose an optical flow algorithm called SimpleFlow whose running times increase sublinearly in the number of pixels. Central to our approach is a probabilistic representation of the motion flow that is computed using only local evidence and without resorting to global optimization. To estimate the flow in image regions where the motion is smooth, we use a sparse set of samples only, thereby avoiding the expensive computation inherent in traditional dense algorithms. We show that our results can be used as is for a variety of video editing tasks. For applications where accuracy is paramount, we use our result to bootstrap a global optimization. This significantly reduces the running times of such methods without sacrificing accuracy. We also demonstrate that the SimpleFlow algorithm can process HD and 4K footage in reasonable times.
BibTeX
@article {10.1111:j.1467-8659.2012.03013.x,
journal = {Computer Graphics Forum},
title = {{SimpleFlow: A Non-iterative, Sublinear Optical Flow Algorithm}},
author = {Tao, Michael and Bai, Jiamin and Kohli, Pushmeet and Paris, Sylvain},
year = {2012},
publisher = {The Eurographics Association and John Wiley and Sons Ltd.},
ISSN = {1467-8659},
DOI = {10.1111/j.1467-8659.2012.03013.x}
}
journal = {Computer Graphics Forum},
title = {{SimpleFlow: A Non-iterative, Sublinear Optical Flow Algorithm}},
author = {Tao, Michael and Bai, Jiamin and Kohli, Pushmeet and Paris, Sylvain},
year = {2012},
publisher = {The Eurographics Association and John Wiley and Sons Ltd.},
ISSN = {1467-8659},
DOI = {10.1111/j.1467-8659.2012.03013.x}
}