论文标题
一个新颖的立体声匹配管道，具有稳健性和未连接的差异搜索范围
A novel stereo matching pipeline with robustness and unfixed disparity search range
论文作者
论文摘要
立体声匹配是各种应用程序的重要基础，但是大多数立体声匹配方法的概括性能较差，并且需要固定的差异搜索范围。此外，当前的立体声匹配方法集中在只有正差异的场景上，但忽略了包含正面和负差异的场景，例如3D电影。在本文中，我们提出了一条新的立体声匹配管道，该管道首先根据双目差异计算半密度的差异图，然后根据单眼提示完成其余部分。新的立体声匹配管道具有以下优点：1）比当前大多数立体声匹配方法具有更好的概括性能； 2）放松固定差异搜索范围的限制； 3）可以处理涉及正差异和负差异的场景，这些场景具有更多的潜在应用，例如3D多媒体和VR/AR中的视图合成。实验结果证明了我们新的立体声匹配管道的有效性。
Stereo matching is an essential basis for various applications, but most stereo matching methods have poor generalization performance and require a fixed disparity search range. Moreover, current stereo matching methods focus on the scenes that only have positive disparities, but ignore the scenes that contain both positive and negative disparities, such as 3D movies. In this paper, we present a new stereo matching pipeline that first computes semi-dense disparity maps based on binocular disparity, and then completes the rest depending on monocular cues. The new stereo matching pipeline have the following advantages: It 1) has better generalization performance than most of the current stereo matching methods; 2) relaxes the limitation of a fixed disparity search range; 3) can handle the scenes that involve both positive and negative disparities, which has more potential applications, such as view synthesis in 3D multimedia and VR/AR. Experimental results demonstrate the effectiveness of our new stereo matching pipeline.
