论文标题
特征法:使用图像相干性的3D模型整流
EigenFairing: 3D Model Fairing using Image Coherence
论文作者
论文摘要
表面通常被建模为3D点的三角形网格,质地与网状面孔相关。 3D点可以是从范围数据中取样的,也可以使用立体声或结构 - 移动算法从一组图像中得出。当点不在真实表面的最大曲率或不连续性的临界点时,网格的脸部不靠近建模的表面。这会导致纹理伪像,并且该模型与一组实际图像并不完全一致,这些图像用于纹理映射其网格。本文提出了一种通过重新定位其顶点来完善3D表面模型的技术,使其与一组观察到的物体图像相干。从多个观点观察到的,质地伪影和与图像的不一致是由于表面贴片的非平面度近似。从角度来看,图像区域用于表示本特征空间中补丁的纹理。特征空间表示捕获了纹理的变化,我们试图最小化。基于从特征空间重建的面部纹理和实际图像的面部纹理之间的差异的相干度量被用来重新定位顶点,以改善模型或改进模型。我们将这种模型改进的技术称为特征法,通过几何和质地上的模型可以更好地近似真实的表面。
A surface is often modeled as a triangulated mesh of 3D points and textures associated with faces of the mesh. The 3D points could be either sampled from range data or derived from a set of images using a stereo or Structure-from-Motion algorithm. When the points do not lie at critical points of maximum curvature or discontinuities of the real surface, faces of the mesh do not lie close to the modeled surface. This results in textural artifacts, and the model is not perfectly coherent with a set of actual images -- the ones that are used to texture-map its mesh. This paper presents a technique for perfecting the 3D surface model by repositioning its vertices so that it is coherent with a set of observed images of the object. The textural artifacts and incoherence with images are due to the non-planarity of a surface patch being approximated by a planar face, as observed from multiple viewpoints. Image areas from the viewpoints are used to represent texture for the patch in Eigenspace. The Eigenspace representation captures variations of texture, which we seek to minimize. A coherence measure based on the difference between the face textures reconstructed from Eigenspace and the actual images is used to reposition the vertices so that the model is improved or faired. We refer to this technique of model refinement as EigenFairing, by which the model is faired, both geometrically and texturally, to better approximate the real surface.