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Video Stereolization: Combining Motion Analysis with User Interaction

机译:视频立体声:将运动分析与用户交互结合

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摘要

We present a semiautomatic system that converts conventional videos into stereoscopic videos by combining motion analysis with user interaction, aiming to transfer as much as possible labeling work from the user to the computer. In addition to the widely used structure from motion (SFM) techniques, we develop two new methods that analyze the optical flow to provide additional qualitative depth constraints. They remove the camera movement restriction imposed by SFM so that general motions can be used in scene depth estimationȁ4;the central problem in mono-to-stereo conversion. With these algorithms, the user''s labeling task is significantly simplified. We further developed a quadratic programming approach to incorporate both quantitative depth and qualitative depth (such as these from user scribbling) to recover dense depth maps for all frames, from which stereoscopic view can be synthesized. In addition to visual results, we present user study results showing that our approach is more intuitive and less labor intensive, while producing 3D effect comparable to that from current state-of-the-art interactive algorithms.
机译:我们提出了一种半自动系统,该系统通过将运动分析与用户交互结合起来,将常规视频转换为立体视频,旨在将尽可能多的标签工作从用户转移到计算机。除了广泛使用的运动结构(SFM)技术之外,我们还开发了两种新方法来分析光流,以提供附加的定性深度约束。它们消除了SFM施加的摄像机移动限制,因此可以将一般运动用于场景深度估计中[4];这是单声道到立体声转换的核心问题。使用这些算法,可以大大简化用户的标记任务。我们进一步开发了一种二次编程方法,以结合定量深度和定性深度(例如来自用户的划线),以恢复所有帧的密集深度图,从而可以合成立体视图。除了视觉效果,我们还提供了用户研究结果,这些结果表明我们的方法更直观,劳动强度更低,同时产生的3D效果可与当前最新的交互式算法相媲美。

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