A Photogrammetry-based Framework to Facilitate Image-based Modeling and Automatic Camera Tracking
This framework provides a more efficient workflow for 3D artists and modelers by automating complex photogrammetry tasks within Blender.
This paper presents a Blender framework that integrates Structure from Motion (SfM) and Multi-View Stereo (MVS) to automate camera motion determination and dense scene model computation, tasks not natively supported by Blender's built-in tools.
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.