GGG - Rough or Noisy? Metrics for Noise Detection in SfM Reconstructions

The proposed dataset is part of the paper with the same name "Rough or Noisy? Metrics for Noise Detection in SfM Reconstructions", which proposes 9 geometrical and SfM capturing setup metrics for training a classification method for detecting noise on a SfM reconstructed surfaces.

The dataset contains images for Structure from Motion reconstruction of 15 objects. The images were taken using a Canon 5Ds DSLR camera with a resolution of 8688x5792. The images contain EXIF data that can be used to assist the 3D reconstruction. For all objects, except the wind turbine blade the images are 36 in a circle around the object. For the wind turbine blade the images are positioned in 2 vertical bands of 17 images each in a semi-circle.

Together with the images there are reconstruction point clouds. These are created using Agisoft Metashape (Photoscan). For easier processing they are separated into:
- one file containing vertex positions in X,Y,Z column stacked format, together with color for each vertex position in RGB
- one file containing the normals in Nx, Ny, Nz column stacked format
- one file containing triangulated faces for the used vertices

Finally there are manually annotated ground truth segmentations of the point clouds into noise and not noise for each of the 15 objects.

所提出的数据集系同一名称论文《粗糙或噪声？SfM重建中噪声检测的度量指标》的组成部分，该论文提出了9个几何和SfM捕捉设置度量指标，旨在训练一种用于检测SfM重建表面噪声的分类方法。该数据集包含15个物体的运动结构重建图像。图像使用具有8688x5792分辨率的佳能5Ds DSLR相机拍摄。图像包含可辅助三维重建的EXIF数据。对于所有物体，除了风力涡轮机叶片，图像环绕物体呈圆形排列，共36张。对于风力涡轮机叶片，图像位于两个垂直的半圆形带中，每个带包含17张图像。与图像一同提供的还有使用Agisoft Metashape（Photoscan）创建的重建点云。为了便于处理，它们被分为以下几类：一个包含X、Y、Z列堆叠格式的顶点位置文件，以及每个顶点位置的RGB颜色信息；一个包含Nx、Ny、Nz列堆叠格式的法线文件；一个包含用于顶点的三角化面的文件。最终，对于这15个物体中的每一个，还提供了手动标注的地面真实分割，将点云分割为噪声和非噪声。