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Depth-Aware Stereo Video Retargeting

机译:深度感知立体声视频重定向

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摘要

As compared with traditional video retargeting, stereo video retargeting poses new challenges because stereo video contains the depth information of salient objects and its time dynamics. In this work, we propose a depth-aware stereo video retargeting method by imposing the depth fidelity constraint. The proposed depth-aware retargeting method reconstructs the 3D scene to obtain the depth information of salient objects. We cast it as a constrained optimization problem, where the total cost function includes the shape, temporal and depth distortions of salient objects. As a result, the solution can preserve the shape, temporal and depth fidelity of salient objects simultaneously. It is demonstrated by experimental results that the depth-aware retargeting method achieves higher retargeting quality and provides better user experience.
机译:与传统视频重定向相比,立体声视频重定向提出了新的挑战,因为立体声视频包含显着对象的深度信息及其时间动态。在这项工作中,我们通过施加深度保真度约束,提出了一种深度感知的立体声视频重定向方法。提出的深度感知重定位方法重建3D场景以获得显着物体的深度信息。我们将其转换为约束优化问题,其中总成本函数包括显着对象的形状,时间和深度变形。结果,该解决方案可以同时保留突出对象的形状,时间和深度保真度。实验结果表明,深度感知重定目标方法可以实现更高的重定目标质量并提供更好的用户体验。

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