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Depth propagation for semi-automatic 2D to 3D conversion

机译:半自动2D到3D转换的深度传播

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In this paper, we present a method for temporal propagation of depth data that is available for so called key-frames through video sequence. Our method requires that full frame depth information is assigned. Our method utilizes nearest preceding and nearest following key-frames with known depth information. The propagation of depth information from two sides is essential as it allows to solve most occlusion problems correctly. Image matching is based on the coherency sensitive hashing (CSH) method and is done using image pyramids. Disclosed results are compared with temporal interpolation based on motion vectors from optical flow algorithm. The proposed algorithm keeps sharp depth edges of objects even in situations with fast motion or occlusions. It also handles well many situations, when the depth edges don't perfectly correspond with true edges of objects.
机译:在本文中,我们介绍了一种用于通过视频序列所谓的键帧可用的深度数据的时间传播方法。我们的方法要求分配全帧深度信息。我们的方法利用最近的前面和最近的键帧,具有已知深度信息。从两侧的深度信息传播至关重要,因为它允许正确地解决大多数遮挡问题。图像匹配基于一致性敏感散列(CSH)方法,并使用图像金字塔完成。将所公开的结果与基于光流算法的运动矢量进行了比较的结果。所提出的算法即使在具有快速运动或闭塞的情况下也可以保持物体的尖锐深度边缘。当深度边缘与对象的真正边缘不完全对应时,它还处理许多情况。

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