Shrinkability Maps for Content-Aware Video Resizing
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Date
2008
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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.
Description
@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}
}