Secrets of adaptive support weight techniques for local stereo matching
Secrets of adaptive support weight techniques for local stereo matching
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DOI：
10.1016/j.cviu.2013.01.007
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发表时间：
2013-06-01
影响因子：
4.5
通讯作者：
Gelautz, Margrit
中科院分区：
文献类型：
--
作者：
Hosni, Asmaa;Bleyer, Michael;Gelautz, Margrit
近年来，局部立体匹配算法在立体视觉领域再次变得非常流行。这主要是由于引入了自适应支持权重算法，该算法可以首次产生与全局立体方法相当的结果。这些自适应支持权重方法的关键是为支持窗口内的每个像素分配单独的权重。自适应支持权重算法的不同主要在于这种权重计算的方式进行。在本文中，我们提出了一个广泛的评价研究。我们评估各种方法的性能计算自适应支持权重，包括原来的双边过滤器为基础的权重，以及最近的方法的基础上测地线距离或指导过滤器。为了获得可靠的结果，我们在35个地面真实差异对的大集合上测试了这些不同的权重函数。我们已经在GPU上实现了所有方法，这允许在现代硬件平台上公平比较运行时间。除了标准的本地匹配使用正面平行窗口，我们还嵌入到最近的PatchMatch立体方法，它使用倾斜的子像素窗口，并代表了一个国家的最先进的本地算法的竞争权重函数。在本文的最后一部分，我们的目的是阐明一般点的自适应支持权重匹配，其中，例如，包括对称与不对称的支持权重的方法进行了讨论。(c)2013 Elsevier Inc. All rights reserved.
In recent years, local stereo matching algorithms have again become very popular in the stereo community. This is mainly due to the introduction of adaptive support weight algorithms that can for the first time produce results that are on par with global stereo methods. The crux in these adaptive support weight methods is to assign an individual weight to each pixel within the support window. Adaptive support weight algorithms differ mainly in the manner in which this weight computation is carried out.In this paper we present an extensive evaluation study. We evaluate the performance of various methods for computing adaptive support weights including the original bilateral filter-based weights, as well as more recent approaches based on geodesic distances or on the guided filter. To obtain reliable findings, we test these different weight functions on a large set of 35 ground truth disparity pairs. We have implemented all approaches on the GPU, which allows for a fair comparison of run time on modern hardware platforms. Apart from the standard local matching using fronto-parallel windows, we also embed the competing weight functions into the recent PatchMatch Stereo approach, which uses slanted sub-pixel windows and represents a state-of-the-art local algorithm. In the final part of the paper, we aim at shedding light on general points of adaptive support weight matching, which, for example, includes a discussion about symmetric versus asymmetric support weight approaches. (c) 2013 Elsevier Inc. All rights reserved.