Object-Ratio-Preserving Video Retargeting Framework based on Segmentation and Inpainting

Jun-Gyu Jin, Jaehyun Bae, Han-Gyul Baek, Sang-hyo Park
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引用次数: 3

Abstract

The recent development of video-based content platforms led the easy access to videos decades ago. However, some past videos have a old screen ratio. If an image with this ratio is executed on a display with a wider screen ratio, the image is excessively stretched horizontally or creates a black box, which prevents efficient viewing of content. In this paper, we propose a method for retargeting the old ratio video frames to a wider ratio while maintaining the original ratio of important objects in content using deep learning-based semantic segmentation and inpainting techniques. Our research shows that proposed method can make a retargeted frames visually natural.
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基于分割和补画的保持目标比例的视频重定向框架
最近基于视频的内容平台的发展使得几十年前的视频访问变得容易。然而,一些过去的视频有一个旧的屏幕比例。如果在具有更宽屏幕比例的显示器上执行具有此比率的图像,则图像会过度横向拉伸或创建黑框,从而妨碍有效地查看内容。在本文中,我们提出了一种方法,该方法使用基于深度学习的语义分割和绘图技术,将旧的比例视频帧重新定位到更宽的比例,同时保持内容中重要对象的原始比例。研究表明,该方法可以使重定向帧在视觉上更加自然。
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