Zhang Guofeng, Hua Wei, Qin Xueying, Wong Tien-Tsin, Bao Hujun
State Key Lab of CAD & CG, Zhejiang University, Hangzhou, PR China.
IEEE Trans Vis Comput Graph. 2007 Jul-Aug;13(4):686-96. doi: 10.1109/TVCG.2007.1032.
This paper presents an automatic and robust approach to synthesize stereoscopic videos from ordinary monocular videos acquired by commodity video cameras. Instead of recovering the depth map, the proposed method synthesizes the binocular parallax in stereoscopic video directly from the motion parallax in monocular video. The synthesis is formulated as an optimization problem via introducing a cost function of the stereoscopic effects, the similarity, and the smoothness constraints. The optimization selects the most suitable frames in the input video for generating the stereoscopic video frames. With the optimized selection, convincing and smooth stereoscopic video can be synthesized even by simple constant-depth warping. No user interaction is required. We demonstrate the visually plausible results obtained given the input clips acquired by ordinary handheld video camera.
本文提出了一种自动且稳健的方法,可从商用摄像机获取的普通单目视频合成立体视频。该方法并非恢复深度图,而是直接从单目视频中的运动视差合成立体视频中的双目视差。通过引入立体效果、相似度和平滑度约束的代价函数,将合成过程表述为一个优化问题。该优化在输入视频中选择最合适的帧来生成立体视频帧。通过这种优化选择,即使采用简单的恒定深度扭曲,也能合成令人信服且平滑的立体视频,无需用户交互。我们展示了使用普通手持摄像机获取的输入片段所得到的视觉上合理的结果。