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Full Frame Video Stabilization Using Motion Inpainting

机译:使用运动修补实现全帧视频稳定

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摘要

The amount of video data has increased dramatically with the advent of digital imaging. Most of the video captured these days originates from a mobile phones and handheld video cameras. Such videos are shaky compared to videos that are shot with a tripod mounted camera. Stabilizing this video to remove the shaky effect using software is called Digital video stabilization which results in a stable and visually pleasant video. In order digitally stabilize the image, we need to (1) Estimate the motion of camera, (2) Regenerate the motion of camera without the undesirable artifacts and (3) Synthesize new video frames. This dissertation is targeted at improving the last two steps of stabilizing the video. Most of the previous techniques of video stabilization produce a lower resolution stabilized video output and clip portions of frames to remove the empty area formed by transformation of the video frames. We use a Gaussian averaging filter to smoother the global motion in the video. Then the frames are transformed using the new transformation matrices obtained by subtracting the original transformation chain from the modified transformation chain. For the last step of synthesizing new video frames, we introduce an improved completion technique which can produce full frame video by using the pixel information from nearby frames to estimate the intensity of the missing pixels. This technique uses motion inpainting to ensure that the video frames are filled in both the static image area and dynamic image area with the same consistency. Additionally, the quality of the video is improved by using a deblurring algorithm which further improves the smoothness of video by eliminating undesirable motion blur. We do not estimate the PSF, in its place, we transfer and interpolate the sharper pixels from nearby frames to improve the sharpness and deblur current frame. Completing the video with motion inpainting and deblurring technique allow us to construct a full frame video stabilization system with good image quality. This is verified by implementing the technique on different video sequences.
机译:随着数字成像的出现,视频数据量急剧增加。这些天捕获的大多数视频来自手机和手持摄像机。与使用安装在三脚架上的相机拍摄的视频相比,此类视频比较不稳定。使用软件稳定该视频以消除晃动的效果称为数字视频稳定,可以产生稳定且视觉上令人愉悦的视频。为了数字稳定图像,我们需要(1)估计摄像机的运动,(2)再生摄像机的运动而没有不希望的伪影,以及(3)合成新的视频帧。本文的目的是改进视频稳定的最后两个步骤。视频稳定的大多数先前技术产生了较低分辨率的稳定视频输出,并剪辑了帧的一部分,以消除由视频帧的转换形成的空白区域。我们使用高斯平均滤波器来平滑视频中的全局运动。然后,使用通过从修改的转换链中减去原始转换链而获得的新转换矩阵对帧进行转换。对于合成新视频帧的最后一步,我们引入了一种改进的完成技术,该技术可以通过使用附近帧中的像素信息来估计丢失像素的强度来生成全帧视频。该技术使用运动修补来确保视频帧以相同的一致性填充到静态图像区域和动态图像区域中。另外,通过使用去模糊算法提高了视频质量,该算法通过消除不希望的运动模糊进一步提高了视频的平滑度。我们不估计PSF取而代之,而是从附近的帧中传输和内插更清晰的像素,以改善清晰度和对当前帧进行模糊处理。使用运动修复和去模糊技术来完成视频的制作,使我们能够构建具有良好图像质量的全帧视频稳定系统。通过在不同的视频序列上实施该技术可以验证这一点。

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    Sandeep Manthi Venkat;

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  • 年度 2015
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