FAUST-partial is a 3D registration benchmark dataset created to address the lack of data variability in the existing 3D registration benchmarks such as: 3DMatch, ETH, KITTI.
The original FAUST training dataset is comprised of 100 3D scans of human bodies.
The benchmark generation for a single scan from the FAUST training dataset can be summarized as follows: 1. Make xz-plane the floor by translating the minimal bounding box point of the scan to the origin 2. Surround the scan with a regular icosahaedron. Each point of the icosahaedron acts as a viewpoint 3. For each viewpoint, create a partial point cloud using the hidden point removal algorithm
Finally, for a pair of partial point clouds with the desired overalp, generate a random rotation from the desired rotation range and translation range.
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FAUST-partial (60%+ overlap, Rot 0-45, Trans -50-50, trained on 3DMatch)
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