GGG-BenchmarkSfM: Dataset for Benchmarking Close-range SfM Software Performance under Varying Capturing Conditions

The proposed dataset aims to benchmark the performance of SfM software under varying conditions - different environments, different lighting, image positions, camera setups, etc. Images of six objects are provided with varying shapes, sizes, surface textures and materials. The dataset is divided in two main parts, together with ReadMe files:
- Objects and environments data - images from each of the objects both from indoor and outdoor environments are provided.
- Capturing setups data - images from one of the objects are provided captured with different setups. Both with and without using a turntable, using one and multiple light sources and different amount of images

All images are captured using Canon 6D DSLR camera. All images contain EXIF data with used camera parameters. A ground truth high resolution scanned of each of the objects is provided for verifying the accuracy of the SfM reconstructions.

本数据集旨在针对不同环境、光照条件、拍摄点位与相机配置等多样工况，对运动恢复结构（Structure from Motion，简称SfM）软件的性能开展基准测试。数据集涵盖6类具备差异化形状、尺寸、表面纹理与材质的物体的拍摄图像。
本数据集附带ReadMe文档，并分为两大核心模块：
- 物体与环境数据模块：提供全部6类物体在室内、室外两种环境下的拍摄图像。
- 拍摄配置数据模块：选取其中1类物体，提供多种配置下的拍摄图像，涵盖是否使用转台、单光源/多光源照明，以及不同拍摄张数的拍摄场景。

所有图像均采用佳能6D单反相机拍摄，且均包含记录了拍摄参数的EXIF（Exchangeable Image File Format）元数据。本数据集同时提供每类物体的高精度扫描真值模型，用于验证SfM重建结果的精度。