Geometrica Research Group, INRIA Sophia Antipolis, 2004 route des Lucioles, Sophia Antipolis 06902, France.
IEEE Trans Pattern Anal Mach Intell. 2013 Jan;35(1):5-17. doi: 10.1109/TPAMI.2012.84.
We present an original multiview stereo reconstruction algorithm which allows the 3D-modeling of urban scenes as a combination of meshes and geometric primitives. The method provides a compact model while preserving details: Irregular elements such as statues and ornaments are described by meshes, whereas regular structures such as columns and walls are described by primitives (planes, spheres, cylinders, cones, and tori). We adopt a two-step strategy consisting first in segmenting the initial meshbased surface using a multilabel Markov Random Field-based model and second in sampling primitive and mesh components simultaneously on the obtained partition by a Jump-Diffusion process. The quality of a reconstruction is measured by a multi-object energy model which takes into account both photo-consistency and semantic considerations (i.e., geometry and shape layout). The segmentation and sampling steps are embedded into an iterative refinement procedure which provides an increasingly accurate hybrid representation. Experimental results on complex urban structures and large scenes are presented and compared to state-of-the-art multiview stereo meshing algorithms.
我们提出了一种新颖的多视图立体重建算法，可将城市场景的 3D 建模作为网格和几何基元的组合。该方法提供了一个紧凑的模型，同时保留了细节：不规则元素（如雕像和装饰品）用网格描述，而规则结构（如柱和墙）用基元（平面、球体、圆柱体、圆锥体和圆环体）描述。我们采用了两步策略，首先使用基于多标签马尔可夫随机场的模型对初始基于网格的表面进行分割，其次通过 Jump-Diffusion 过程在获得的分区上同时对基元和网格组件进行采样。重建质量通过多目标能量模型进行测量，该模型同时考虑了照片一致性和语义考虑因素（即，几何形状和形状布局）。分割和采样步骤被嵌入到迭代细化过程中，该过程提供了越来越准确的混合表示。呈现了复杂的城市结构和大型场景的实验结果，并与最先进的多视图立体网格算法进行了比较。
