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Semi-automatic 2D-to-3D video conversion based on background sprite generation

机译:基于背景精灵生成的半自动2D到3D视频转换

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This paper presents a new technique for semi-automatic 2D to 3D stereo video conversion. Our algorithm escapes the scope of traditional depth propagation paradigm based on motion estimation and compensation. First of all, we treat the foreground and background depths separately and then combine them to form a final depth map for each video frame. For the foreground parts, they are first segmented out and given the region labels and depths for the two bounding key frames in a human interactive manner. The foreground region labels are then propagated to the intermediate non-key frames to construct the GMM models for foreground segmentation based on the well-known graph-cut algorithm. For the background parts, all video frames are integrated into a background sprite model (BSM), even for a moving camera, based on the image registration algorithm. Users can then draw detailed depth profiles for the integral BSM, thus reducing the human efforts required significantly. Experimental results show that our method is capable of retaining a more complete foreground contour and smooth background variation in depths than prior literature. This advantage is obviously helpful in view synthesis for 3D display and perception.
机译:本文提出了一种新的半自动2D到3D立体声视频转换技术。我们的算法摆脱了基于运动估计和补偿的传统深度传播范例的范围。首先,我们分别处理前景和背景深度,然后将它们组合起来以形成每个视频帧的最终深度图。对于前景部分,首先将它们分割出来,然后以人机交互的方式为两个边界关键帧指定区域标签和深度。然后将前景区域标签传播到中间非关键帧,以基于众所周知的图割算法构建用于前景分割的GMM模型。对于背景部分,基于图像配准算法,所有视频帧,甚至对于移动的摄像机,都集成到背景精灵模型(BSM)中。然后,用户可以绘制出完整的BSM的详细深度轮廓,从而大大减少了所需的人力。实验结果表明,与现有文献相比,我们的方法能够保留更完整的前景轮廓和平滑的深度背景变化。这个优势显然有助于3D显示和感知的视图合成。

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