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Multiflash Stereopsis: Depth-Edge-Preserving Stereo with Small Baseline Illumination

机译:Multiflash立体视觉:具有较小基线照明的深度边缘保留立体视觉

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Traditional stereo matching algorithms are limited in their ability to produce accurate results near depth discontinuities, due to partial occlusions and violation of smoothness constraints. In this paper, we use small baseline multi-flash illumination to produce a rich set of feature maps that enable acquisition of discontinuity preserving point correspondences. First, from a single multi-flash camera, we formulate a qualitative depth map using a gradient domain method that encodes object relative distances. Then, in a multiview setup, we exploit shadows created by light sources to compute an occlusion map. Finally, we demonstrate the usefulness of these feature maps by incorporating them into two different dense stereo correspondence algorithms, the first based on local search and the second based on belief propagation. Experimental results show that our enhanced stereo algorithms are able to extract high quality, discontinuity preserving correspondence maps from scenes that are extremely challenging for conventional stereo methods. We also demonstrate that small baseline illumination can be useful to handle specular reflections in stereo imagery. Different from most existing active illumination techniques, our method is simple, inexpensive, compact, and requires no calibration of light sources.
机译:由于部分遮挡和违反平滑度约束,传统的立体声匹配算法在深度不连续附近产生准确结果的能力受到限制。在本文中,我们使用小型基线多闪光灯照明来生成一组丰富的特征图,这些特征图使得能够获取不连续性保留点对应关系。首先,我们从一台多闪光灯照相机中,使用对物体相对距离进行编码的梯度域方法来制定定性深度图。然后,在多视图设置中,我们利用光源创建的阴影来计算遮挡图。最后,我们通过将这些特征图合并到两个不同的密集立体对应算法中(第一个基于局部搜索,第二个基于置信度传播)证明了它们的有用性。实验结果表明,我们增强的立体算法能够从场景中提取高质量,不连续的对应图,这对于传统的立体方法来说是极具挑战性的。我们还证明了小的基线照明对于处理立体影像中的镜面反射很有用。与大多数现有的主动照明技术不同,我们的方法简单,廉价,紧凑,并且不需要校准光源。

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