Image-based 3D object modeling refers to the process of converting raw optical images to 3D digital representations of the objects. Very often, such models are desired to be dimensionally true, semantically labeled with photorealistic appearance (reality-based modeling). Laser scanning was deemed as the standard (and direct) way to obtaining highly accurate 3D measurements of objects, while one would have to abide the high acquisition cost and its unavailability on some of the platforms. Nowadays the image-based methods backboned by the recently developed advanced dense image matching algorithms and geo-referencing paradigms, are becoming the dominant approaches, due to its high flexibility, availability and low cost. The largely automated geometric processing of images in a 3D object reconstruction workflow, from ordered/unordered raw imagery to textured meshes, is becoming a critical part of the reality-based 3D modeling. This article summarizes the overall geometric processing workflow, with focuses on introducing the state-of-the-art methods of three major components of geometric processing: 1) geo-referencing; 2) Image dense matching 3) texture mapping. Finally, we will draw conclusions and share our outlooks of the topics discussed in this article.
翻译:基于图像的 3D 对象建模是指将原始光学图像转换为 3D 物体数字表达式的过程。 通常,这类模型需要具有维度真实性,以光现实性外观(基于真实性的建模)为标志。 激光扫描被视为获得高度精确的 3D 天体测量的标准(和直接)方式,而人们必须坚持高额的获取成本和某些平台上无法获得这种测量。 如今,由最近开发的高级密集图像匹配算法和地理参照模式支撑的图像方法正在成为主导方法,因为其灵活性、可用性和成本都很低。 3D 对象重建工作流程中的图像基本上自动地几何处理,从有秩序的/无秩序的原始图像到纹理的草模,正在成为基于现实的3D 3D 模型的关键部分。 文章概述了总体的几何处理工作流程,重点是引入三个主要几何处理部件的最新技术方法:(1) 地理参照;(2) 图像密度匹配 3 文本绘图。 最后,我们将在文章中做出结论并分享我们讨论的专题展望。