论文标题
多视图几何形状：基于代数属性的对应关系的改进
Multi-view Geometry: Correspondences Refinement Based on Algebraic Properties
论文作者
论文摘要
对应关系估计或特征匹配是基于图像的3D重建问题的关键步骤。在本文中，我们提出了两个代数特性以进行对应关系。第一个是从两个图像上至少九个关键点的对应关系（两视图对应关系）中的等级缺陷矩阵构造，第二个是从至少五个图像上的六个密钥点的其他对应关系中构建的另一个等级缺陷矩阵（多视图通信）。据我们所知，本文之前的多视图对应关系没有理论上的结果。为了获得准确的对应关系，多视图对应关系似乎比两视图对应关系更有用。从这两个代数特性中，我们提出了对应关系的改进算法。该算法是对应关系改进，离群值识别和缺少密钥点恢复的组合。重建佛像的项目的实际实验表明，在对应关系估计中，提出的改进算法可以将平均误差从77像素减少到55个像素。这种下降是大量的，它验证了我们的结果。
Correspondences estimation or feature matching is a key step in the image-based 3D reconstruction problem. In this paper, we propose two algebraic properties for correspondences. The first is a rank deficient matrix construct from the correspondences of at least nine key-points on two images (two-view correspondences) and the second is also another rank deficient matrix built from the other correspondences of six key-points on at least five images (multi-view correspondences). To our knowledge, there are no theoretical results for multi-view correspondences prior to this paper. To obtain accurate correspondences, multi-view correspondences seem to be more useful than two-view correspondences. From these two algebraic properties, we propose an refinement algorithm for correspondences. This algorithm is a combination of correspondences refinement, outliers recognition and missing key-points recovery. Real experiments from the project of reconstructing Buddha statue show that the proposed refinement algorithm can reduce the average error from 77 pixels to 55 pixels on the correspondences estimation. This drop is substantial and it validates our results.
