Shrinkability Maps for Content-Aware Video Resizing

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Date
2008
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Publisher
The Eurographics Association and Blackwell Publishing Ltd
Abstract
A novel method is given for content-aware video resizing, i.e. targeting video to a new resolution (which may involve aspect ratio change) from the original.We precompute a per-pixel cumulative shrinkability map which takes into account both the importance of each pixel and the need for continuity in the resized result. (If both x and y resizing are required, two separate shrinkability maps are used, otherwise one suffices). A random walk model is used for efficient offline computation of the shrinkability maps. The latter are stored with the video to create a multi-sized video, which permits arbitrary-sized new versions of the video to be later very efficiently created in real-time, e.g. by a video-on-demand server supplying video streams to multiple devices with different resolutions. These shrinkability maps are highly compressible, so the resulting multi-sized videos are typically less than three times the size of the original compressed video. A scaling function operates on the multi-sized video, to give the new pixel locations in the result, giving a high-quality content-aware resized video.Despite the great efficiency and low storage requirements for our method, we produce results of comparable quality to state-of-the-art methods for content-aware image and video resizing.
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@article{
10.1111:j.1467-8659.2008.01325.x
, journal = {Computer Graphics Forum}, title = {{
Shrinkability Maps for Content-Aware Video Resizing
}}, author = {
Zhang, Yi-Fei
and
Hu, Shi-Min
and
Martin, Ralph R.
}, year = {
2008
}, publisher = {
The Eurographics Association and Blackwell Publishing Ltd
}, ISSN = {
1467-8659
}, DOI = {
10.1111/j.1467-8659.2008.01325.x
} }
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