Department of Computer Science and Information Engineering, National Cheng Kung University, No. 1 Daxue Rd., East Dist., Tainan 701, Taiwan, R.O.C.
IEEE Trans Vis Comput Graph. 2013 Oct;19(10):1677-86. doi: 10.1109/TVCG.2013.75.
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 contents 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 overdeformations on low-significance objects, yielding a pleasing motion-aware video retargeting. Qualitative and quantitative analyses, including a user study and experiments on complex videos containing diverse cameras and dynamic motions, show a clear superiority of our method over related video retargeting methods.
提出了一种新的基于内容感知的视频重定目标方法。该技术的关键是在保持视觉显著内容和时间连贯性的同时，将视频适配到具有不同纵横比和大小的显示器。大多数先前的研究通过在帧中一致地调整内容大小来解决这个时空问题。虽然这种策略显著改善了重定目标的结果，但它没有充分考虑对象的保留，有时会导致视觉显著对象出现明显的失真。我们提出了一种基于对象的重要性估计的对象保留变形方案，以减少这种不愉快的失真。在提出的方案中，3D 时空中的视觉显著对象被强制进行尽可能刚性的变形，而低重要性的内容则尽可能接近线性缩放进行变形。这些策略使我们的方法能够一致地保留视觉显著对象的空间形状和时间运动，避免对低重要性对象的过度变形，从而实现令人愉悦的运动感知视频重定目标。包括用户研究和对包含不同相机和动态运动的复杂视频的实验在内的定性和定量分析表明，我们的方法明显优于相关的视频重定目标方法。
