Shrinkability maps for content-aware video resizing

Zhang, Yi-Fei, Hu, Shi-Min ORCID: https://orcid.org/0000-0001-7507-6542 and Martin, Ralph Robert 2008. Shrinkability maps for content-aware video resizing. Computer Graphics Forum 27 (7) , pp. 1797-1804. 10.1111/j.1467-8659.2008.01325.x

Full text not available from this repository.

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.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Computer Science & Informatics
Subjects:	Q Science > QA Mathematics > QA76 Computer software
Uncontrolled Keywords:	I.4.10 [Computing Methodologies]: Image Processing And Computer Visio
Publisher:	Blackwell
ISSN:	0167-7055
Funders:	EPSRC
Last Modified:	17 Oct 2022 09:42
URI:	https://orca.cardiff.ac.uk/id/eprint/5283

Citation Data

Cited 86 times in Scopus. View in Scopus. Powered By Scopus® Data

Actions (repository staff only)

Edit Item