This paper presents a technique for semi-automatic 2D-to-3D stereo video conversion, which is known to provide user intervention in assigning foreground/background depths for key frames and then get depth maps for non-key frames via automatic depth propagation. Our algorithm treats foreground and background separately. For foregrounds, kernel pixels are identified and then used as the seeds for graph-cut segmentation for each non-key frame independently, resulting in results not limited by objects’ motion activity. For backgrounds, all video frames, after foregrounds being removed, are integrated into a common background sprite model (BSM) based on a relay-frame-based image registration algorithm. Users can then draw background depths for BSM in an integrated manner, thus reducing human efforts significantly. Experimental results show that our method is capable of retaining more faithful foreground depth boundaries (by 1.6–2.7 dB) and smoother background depths than prior works. This advantage is helpful for 3D display and 3D perception.

本文介绍了一种用于半自动2D到3D立体声视频转换的技术，该技术可为用户分配关键帧的前景/背景深度，然后通过自动深度传播获得非关键帧的深度图，从而为用户提供干预。我们的算法分别处理前景和背景。对于前景，将识别内核像素，然后将其用作每个非关键帧的图形切割分割的种子，从而获得不受对象运动活动限制的结果。对于背景，在删除前景后，所有视频帧都将基于基于中继帧的图像配准算法集成到通用背景子画面模型（BSM）中。然后，用户可以以集成方式绘制BSM的背景深度，从而显着减少了人力。实验结果表明，与以前的工作相比，我们的方法能够保留更多忠实的前景深度边界（1.6–2.7 dB）和更平滑的背景深度。此优势有助于3D显示和3D感知。