Colmap学习笔记（一）：Pixelwise View Selection for Unstructured Multi-View Stereo 论文阅读

1. 摘要本文展示一套MVS系统该系统利用非结构化的图片实现鲁棒且稠密的建模。本文的主要贡献是深度和法向量的联合估计用光度和几何先验进行像素筛选多视图几何一致项该项同时进行精修和基于图片的深度和法向量的融合。在标准数据和大尺度网络图片上的实验证明了其在精度、完善性、效率方面的优异性能。2. 引言主要贡献Pixelwise normal estimation embedded into an improved PatchMatch sampling scheme.Pixelwise view selection using triangulation angle, incident angle, and image resolution-based geometric priors.Integration of a \temporal view selection smoothness term.Adaptive window support through bilateral photometric consistency for improved occlusion boundary behavior.Introduction of a multi-view geometric consistency term for simultaneous depth/normal estimation and image-based fusion.Reliable depth/normal filtering and fusion.2. 代码地址github.com/colmap/colmap参考文献COLMAP Pixelwise View Selection for Unstructured Multi-View Stereo - 知乎Pixelwise View Selection for Unstructured Multi-View Stereo