从带有摄像机运动的单目视频中恢复背景和前景的深度

Hu Tian, Bojin Zhuang, Yan Hua, Yanyun Zhao, A. Cai
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引用次数: 3

摘要

在本文中,我们提出了一种深度恢复方法,用于有或没有相机运动的单目视频。将几何信息与运动目标提取相结合,不仅可以恢复背景深度,还可以恢复前景深度。此外,针对快速运动、平移、垂直运动等复杂的摄像机运动,我们提出了一种新的全局运动估计(GME)方法,包括有效的异常值抑制来提取运动目标,实验表明,该方法优于大多数最先进的方法。我们提出的深度恢复方法在四个不同摄像机运动的视频序列上进行了测试。实验结果表明,与现有的深度恢复方法相比,该方法可以获得更精确的背景和前景深度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Recovering depth of background and foreground from a monocular video with camera motion
In this paper we propose a depth recovery approach for monocular videos with or without camera motion. By combining geometric information and moving object extraction, not only the depth of background but also the depth of foreground can be recovered. Furthermore, for cases involving complex camera motion such as fast moving, translating, vertical movement, we propose a novel global motion estimation (GME) method including effective outlier rejection to extract moving objects, and experiments demonstrate that the proposed GME method outperforms most of the state-of-the-art methods. The depth recovery approach we propose is tested on four video sequences with different camera movements. Experimental results show that our approach produces more accurate depth of both background and foreground than existing depth recovery methods.
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