What is Around the Camera?
What is Around the Camera?
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DOI：
10.1109/iccv.2017.553
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发表时间：
2016-11
期刊：
影响因子：
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通讯作者：
Stamatios Georgoulis;Konstantinos Rematas;Tobias Ritschel;Mario Fritz;T. Tuytelaars;L. Gool
中科院分区：
文献类型：
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作者：
Stamatios Georgoulis;Konstantinos Rematas;Tobias Ritschel;Mario Fritz;T. Tuytelaars;L. Gool
单个图像揭示了所拍摄的环境的多少？在本文中，我们研究了可以从前景对象中检索多少信息，并结合背景（即环境的可见部分）。假设它不是完美的扩散，前景对象充当一个复杂形状的且直觉完美的镜子的另一个挑战是，它的外观将来自环境传来的光混淆了它的光。我们提出了一种基于学习的方法，以从近似表面正常的多个反射图中预测环境。提出的方法使我们能够共同对环境和材料特性的统计数据进行建模。我们从合成的培训数据中训练系统，但证明了其对现实数据的适用性。有趣的是，我们的分析表明，从多种材料制成的对象获得的信息通常是互补的，可以提高性能。
How much does a single image reveal about the environment it was taken in? In this paper, we investigate how much of that information can be retrieved from a foreground object, combined with the background (i.e. the visible part of the environment). Assuming it is not perfectly diffuse, the foreground object acts as a complexly shaped andfar-from-perfect mirror An additional challenge is that its appearance confounds the light coming from the environment with the unknown materials it is made of. We propose a learning-based approach to predict the environment from multiple reflectance maps that are computed from approximate surface normals. The proposed method allows us to jointly model the statistics of environments and material properties. We train our system from synthesized training data, but demonstrate its applicability to real-world data. Interestingly, our analysis shows that the information obtained from objects made out of multiple materials often is complementary and leads to better performance.