IEEE Trans Vis Comput Graph - Content-Aware Video Retargeting Using Object-preserving Warping.

Tópicos

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Resumo

A novel content-aware warping approach is introduced for video retargeting. The key to this technique is adapting videos to fit displays with various aspect ratios and sizes while preserving both visually salient content and temporal coherence. Most previous studies solve this spatiotemporal problem by consistently resizing content in frames. This strategy significantly improves the retargeting results, but does not fully consider object preservation, sometimes causing apparent distortions on visually salient objects. We propose an object-preserving warping scheme with object-based significance estimation to reduce this unpleasant distortion. In the proposed scheme, visually salient objects in 3D space-time space are forced to undergo as-rigid-as-possible warping, while low-significance objects are warped as close as possible to linear rescaling. These strategies enable our method to consistently preserve both the spatial shapes and temporal motions of visually salient objects, and avoid over-deformations on low-significance objects, yielding a pleasing motion-aware video retargeting. Qualitative analyses, including a user study with chi-squared test, and experiments on complex videos containing diverse cameras and dynamic motions, show a clear superiority of our method over state-of-the-art video retargeting methods.

Resumo Limpo

novel contentawar warp approach introduc video retarget key techniqu adapt video fit display various aspect ratio size preserv visual salient content tempor coher previous studi solv spatiotempor problem consist resiz content frame strategi signific improv retarget result fulli consid object preserv sometim caus appar distort visual salient object propos objectpreserv warp scheme objectbas signific estim reduc unpleas distort propos scheme visual salient object d spacetim space forc undergo asrigidasposs warp lowsignific object warp close possibl linear rescal strategi enabl method consist preserv spatial shape tempor motion visual salient object avoid overdeform lowsignific object yield pleas motionawar video retarget qualit analys includ user studi chisquar test experi complex video contain divers camera dynam motion show clear superior method stateoftheart video retarget method

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