论文标题
基于摄影测量的框架，可促进基于图像的建模和自动摄像机跟踪
A Photogrammetry-based Framework to Facilitate Image-based Modeling and Automatic Camera Tracking
论文作者
论文摘要
我们提出了一个框架，该框架将搅拌机扩展到从运动（SFM）和多视图立体声（MVS）技术中利用结构，用于基于图像的建模任务，例如雕刻或相机和运动跟踪。应用SFM使我们能够在不手动定义特征轨道或校准用于捕获图像数据的相机的情况下确定相机运动。使用MVS，我们能够自动计算密集的场景模型，这对于搅拌机的内置工具不可行。目前，我们的框架支持几个最先进的SFM和MVS管道。模块化系统设计使我们能够在不付出其他努力的情况下整合进一步的方法。该框架可作为开源软件包公开使用。
We propose a framework that extends Blender to exploit Structure from Motion (SfM) and Multi-View Stereo (MVS) techniques for image-based modeling tasks such as sculpting or camera and motion tracking. Applying SfM allows us to determine camera motions without manually defining feature tracks or calibrating the cameras used to capture the image data. With MVS we are able to automatically compute dense scene models, which is not feasible with the built-in tools of Blender. Currently, our framework supports several state-of-the-art SfM and MVS pipelines. The modular system design enables us to integrate further approaches without additional effort. The framework is publicly available as an open source software package.
