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We introduce a new algorithm for video retargeting that uses discontinuous seam-carving in both space and time for resizing videos. Our algorithm relies on a novel appearance-based temporal coherence formulation that allows for frame-by-frame processing and results in temporally discontinuous seams, as opposed to geometrically smooth and continuous seams. This formulation optimizes the difference...
When the sub-pixel displacement among low- resolution images (LR) is "0.5" unit pixel, current micro-displacement super-resolution (SR) method can reconstruct encouraging high-resolution images (HR). But if actual LR video images are processed in the same way, some severe motion blur will appear in the restored image. Because of the quality difference, a new selection method based on the...
Segmentation of videos into layers of foreground objects and background has many important applications, such as video compression, human computer interaction, and motion analysis. Most existing methods work on image pixels or color segmentations which are computation expensive. Some methods require extensive manual input, static cameras, and/or rigid scenes. In this paper we propose a fully automatic...
In this paper, we propose a learning-based method for video super-resolution. There are two main contributions of the proposed method. First, information from cameras with different spatial-temporal resolutions is combined in our framework. This is achieved by constructing training dictionary using the high resolution images captured by still camera and the low resolution video is enhanced via searching...
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