Robust one-shot 3D scanning using loopy belief propagation
Robust one-shot 3D scanning using loopy belief propagation
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DOI：
10.1109/cvprw.2010.5543556
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发表时间：
2010-06
期刊：
影响因子：
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通讯作者：
Ali O. Ulusoy;Fatih Calakli;G. Taubin
中科院分区：
文献类型：
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作者：
Ali O. Ulusoy;Fatih Calakli;G. Taubin
结构光技术可以大大简化从图像中恢复形状的问题。目前在设计这种技术方面存在两个主要的研究挑战。一个是处理复杂的场景，包括纹理，遮挡，阴影，尖锐的不连续性，在某些情况下，甚至动态变化;另一个是通过需要少量的图像和计算要求较低的算法来加快采集过程。本文提出了一种“一次性”的这种技术的变体，以解决上述挑战。它的工作原理是将静态网格图案投影到场景上，并识别网格条纹与相机图像之间的对应关系。对应的问题，制定了一种新的图形模型，并有效地解决使用循环的信念传播。与现有方法不同，该方法使用非确定性几何约束，从而可以处理条纹图像的虚假连接。在多种复杂的真实的场景中验证了该方法的有效性。
A structured-light technique can greatly simplify the problem of shape recovery from images. There are currently two main research challenges in design of such techniques. One is handling complicated scenes involving texture, occlusions, shadows, sharp discontinuities, and in some cases even dynamic change; and the other is speeding up the acquisition process by requiring small number of images and computationally less demanding algorithms. This paper presents a “one-shot” variant of such techniques to tackle the aforementioned challenges. It works by projecting a static grid pattern onto the scene and identifying the correspondence between grid stripes and the camera image. The correspondence problem is formulated using a novel graphical model and solved efficiently using loopy belief propagation. Unlike prior approaches, the proposed approach uses non-deterministic geometric constraints, thereby can handle spurious connections of stripe images. The effectiveness of the proposed approach is verified on a variety of complicated real scenes.