A System for Retargeting of Streaming Video


We present a novel, integrated system for content-aware video retargeting.

December 17, 2009



Philip Krähenbühl (ETH Zurich)

Manuel Lang (ETH Zurich)

Alexander Sorkine-Hornung (ETH Zurich)

Markus Gross (Disney Research/ETH Zurich)

A System for Retargeting of Streaming Video


A simple and interactive framework combines key frame based constraint editing with numerous automatic algorithms for video analysis. This combination gives content producers high level control of the retargeting process. The central component of our framework is a non-uniform, pixel-accurate warp to the target resolution which considers automatic as well as interactively defined features. Automatic features comprise video saliency, edge preservation at the pixel resolution, and scene cut detection to enforce bilateral temporal coherence. Additional high level constraints can be added by the producer to guarantee a consistent scene composition across arbitrary output formats. For high quality video display we adopted a 2D version of EWA splatting eliminating aliasing artifacts known from previous work. Our method seamlessly integrates into postproduction and computes the reformatting in realtime. This allows us to retarget annotated video streams at a high quality to arbitary aspect ratios while retaining the intended cinematographic scene composition. For evaluation we conducted a user study which revealed a strong viewer preference for our method.

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