Integrating Stereo with Shape-from-Shading derived Orientation Information
Integrating Stereo with Shape-from-Shading derived Orientation Information
复制标题
将立体与阴影形状导出的方向信息相集成
DOI：
--
复制
发表时间：
2007
期刊：
影响因子：
--
通讯作者：
Richard C. Wilson
中科院分区：
文献类型：
--
作者：
T. Haines;Richard C. Wilson
双目立体视觉在提取场景形状方面得到了广泛的研究。挑战在于匹配一个场景的两幅图像之间的特征；这就是对应问题。形状从阴影（SfS）是另一种方法提取形状。这模拟了光与单个图像的场景表面的相互作用。这两种方法非常不同；立体声使用表面特征来提供深度图，SfS使用阴影，反照率和照明信息来推断深度图的差异。在本文中，我们开发了一个深度和方向信息集成的框架。用于初始估计的专用算法。然后用高斯-马尔可夫随机场表示深度图，用高斯信念传播来近似深度图的MAP估计。整合来自立体对应和表面法线的信息，可以估计出精细的表面细节。
Binocular stereo has been extensively studied for extracting the shape of a scene. The challenge is in matching features between two images of a scene; this is the correspondence problem. Shape from shading (SfS) is another method of extracting shape. This models the interaction of light with the scene surface(s) for a single image. These two methods are very different; stereo uses surface features to deliver a depth-map, SfS uses shading, albedo and lighting information to infer the differential of the depth-map. In this paper we develop a framework for the integration of both depth and orientation information. Dedicated algorithms are used for initial estimates. A Gaussian-Markov random field then represents the depth-map, Gaussian belief propagation is used to approximate the MAP estimate of the depth-map. Integrating information from both stereo correspondences and surface normals allows fine surface details to be estimated.