Faster Seam Carving for Video Retargeting

Abstract

Video retargeting is to resize a video to a desired resolution or aspect ratio while preserving its salient content without visual distortion. The key to video retargeting is to reconcile spatio-temporal coherence of video frames, and most existing works use seam carving to achieve that by employing the dynamic programming to find optimal seams. However, these methods are too time-consuming due to high computational complexity of the dynamic programming. To this end, we propose a novel method which uses discontinuous and suboptimal seams for seam carving. Concretely, we obtain the discontinuous seams by allowing seams to move freely in homogeneous regions of the frame, which helps preserve the spatio-temporal coherence effectively. Then, the genetic algorithm is employed to find suboptimal seams, so as to reduce computational complexity. Finally, each frame can be retargeted to a new aspect ratio or size by repeatedly carving out seams. Compared to the-state-of-the-art methods, the proposed algorithm achieves comparable results at an average expense of only one third of their running time.