Accelerating Cost Volume Filtering Using Salient Subvolumes and Robust Occlusion Handling
Accelerating Cost Volume Filtering Using Salient Subvolumes and Robust Occlusion Handling
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DOI：
10.1007/978-3-319-16808-1_22
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发表时间：
2014-11
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影响因子：
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通讯作者：
M. Helala;F. Qureshi
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文献类型：
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作者：
M. Helala;F. Qureshi
计算机视觉中的几个基本问题，如立体深度估计、光流计算等，都可以归结为离散像素标记问题。传统的基于马尔可夫随机场(MRF)的解决方案计算量大。成本量过滤(CF)提供了一种引人注目的替代方案。尽管如此，这些方法必须过滤整个成本，才能得出解决方案。在本文中，我们提出了一种新的基于立体视觉的深度估计方法。首先，我们提出了加速成本量过滤(ACF)方法，该方法识别成本量中的显著子量。筛选仅限于这些子卷，从而显著提高了性能。所提出的方法没有考虑整个成本量，并且导致未标记(遮挡)像素的边际增加。我们通过开发遮挡处理(OH)技术来解决这一问题，该技术使用超像素并通过模拟退火法执行标签传播。我们在Middlebury立体声基准和Middlebury 2005/2006立体数据集的高分辨率图像上对所提出的方法(ACF+OH)进行了评估，我们的方法取得了最先进的结果。我们的遮挡处理方法，当用作后处理步骤时，也显著提高了最近的两种成本量过滤方法的准确性。
Several fundamental computer vision problems, such as depth estimation from stereo, optical flow computation, etc., can be formulated as a discrete pixel labeling problem. Traditional Markov Random Fields (MRF) based solutions to these problems are computationally expensive. Cost Volume Filtering (CF) presents a compelling alternative. Still these methods must filter the entire cost volume to arrive at a solution. In this paper, we propose a new CF method for depth estimation by stereo. First, we propose the Accelerated Cost Volume Filtering (ACF) method which identifies salient subvolumes in the cost volume. Filtering is restricted to these subvolumes, resulting in significant performance gains. The proposed method does not consider the entire cost volume and results in a marginal increase in unlabeled (occluded) pixels. We address this by developing an Occlusion Handling (OH) technique, which uses superpixels and performs label propagation via a simulated annealing inspired method. We evaluate the proposed method (ACF+OH) on the Middlebury stereo benchmark and on high resolution images from Middlebury 2005/2006 stereo datasets, and our method achieves state-of-the-art results. Our occlusion handling method, when used as a post-processing step, also significantly improves the accuracy of two recent cost volume filtering methods.