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Fisheye Video Correction

机译:鱼眼视频校正

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摘要

Various types of video can be captured with fisheye lenses; their wide field of view is particularly suited to surveillance video. However, fisheye lenses introduce distortion, and this changes as objects in the scene move, making fisheye video difficult to interpret. Current still fisheye image correction methods are either limited to small angles of view, or are strongly content dependent, and therefore unsuitable for processing video streams. We present an efficient and robust scheme for fisheye video correction, which minimizes time-varying distortion and preserves salient content in a coherent manner. Our optimization process is controlled by user annotation, and takes into account a wide set of measures addressing different aspects of natural scene appearance. Each is represented as a quadratic term in an energy minimization problem, leading to a closed-form solution via a sparse linear system. We illustrate our method with a range of examples, demonstrating coherent natural-looking video output. The visual quality of individual frames is comparable to those produced by state-of-the-art methods for fisheye still photograph correction.
机译:鱼眼镜头可以捕获各种类型的视频;它们的宽视野特别适合监视视频。但是,鱼眼镜头会产生失真,并且这种失真会随着场景中对象的移动而发生变化,从而使鱼眼镜头视频难以解析。当前的静止鱼眼图像校正方法或者限于小视角,或者强烈依赖于内容,因此不适合处理视频流。我们提出了一种用于鱼眼视频校正的有效且鲁棒的方案,该方案可最大程度地减少随时间变化的失真并以连贯的方式保留突出内容。我们的优化过程由用户注释控制,并考虑了一系列针对自然场景外观不同方面的措施。在能量最小化问题中,每个函数都用二次项表示,从而通过稀疏线性系统得出闭式解。我们通过一系列示例来说明我们的方法,以演示连贯自然的视频输出。单个帧的视觉质量与通过最先进的鱼眼静态照片校正方法所产生的视觉质量相当。

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