Combining Shape from Shading and Stereo: A Variational Approach for the Joint Estimation of Depth, Illumination and Albedo
Combining Shape from Shading and Stereo: A Variational Approach for the Joint Estimation of Depth, Illumination and Albedo
复制标题
结合阴影和立体的形状：联合估计深度、光照和反照率的变分方法
DOI：
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发表时间：
2016
期刊：
影响因子：
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通讯作者：
Andrés Bruhn
中科院分区：
文献类型：
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作者：
Daniel Maurer;Y. Ju;M. Breuß;Andrés Bruhn
明暗恢复形状（SfS）和立体是基于图像的三维重建的两种根本不同的策略。虽然SfS的方法仅从像素强度推断深度，但立体方法基于在图像之间建立对应关系的匹配过程。在本文中，我们提出了一个联合变分方法，结合了这两种策略的优点。通过将最近的立体声和SfS模型集成到一个单一的最小化框架中，我们获得了一种利用阴影信息来提高鲁棒立体声方法的重建质量的方法。为此，我们融合了朗伯SfS方法与一个强大的立体声模型，并补充所产生的能量泛函与细节保持各向异性二阶平滑项。此外，我们扩展了新的模型，以这样一种方式，它联合估计深度，亮度和照明。这反过来又使其适用于具有非均匀光照的对象以及具有未知照明的场景。合成和真实世界的图像的实验表明，我们的组合方法的优点：虽然立体部分克服了所有SfS方法固有的深度模糊性，SfS部分提高了重建的细节程度相比，纯立体方法。
Shape from shading (SfS) and stereo are two fundamentally different strategies for image-based 3-D reconstruction. While approaches for SfS infer the depth solely from pixel intensities, methods for stereo are based on a matching process that establishes correspondences across images. In this paper we propose a joint variational method that combines the advantages of both strategies. By integrating recent stereo and SfS models into a single minimisation framework, we obtain an approach that exploits shading information to improve upon the reconstruction quality of robust stereo methods. To this end, we fuse a Lambertian SfS approach with a robust stereo model and supplement the resulting energy functional with a detail-preserving anisotropic second-order smoothness term. Moreover, we extend the novel model in such a way that it jointly estimates depth, albedo and illumination. This in turn makes it applicable to objects with non-uniform albedo as well as to scenes with unknown illumination. Experiments for synthetic and real-world images show the advantages of our combined approach: While the stereo part overcomes the albedo-depth ambiguity inherent to all SfS methods, the SfS part improves the degree of details of the reconstruction compared to pure stereo methods.
DOI：
10.1109/iccv.2011.6126359
发表时间：
2011
期刊：
2011 International Conference on Computer Vision
影响因子：
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作者：
S. Volz;A. Bruhn;L. Valgaerts;H. Zimmer
通讯作者：
H. Zimmer
一种用于阴影变化透视形状的有效线性化方法
DOI：
10.1007/978-3-319-24947-6_20
发表时间：
2015
期刊：
影响因子：
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作者：
D. Maurer;Y.-C. Ju;M. Breuß;A. Bruhn
通讯作者：
A. Bruhn