Reconstruction system (Tensor)¶

This tutorial demonstrates volumetric RGB-D reconstruction and dense RGB-D SLAM with the Open3D Tensor interface and the Open3D Hash map backend.

It is possible to run the tutorial with the minimalistic dataset in examples/test_data/RGBD, but it is recommended to run the tutorial with real-world datasets with longer sequences to demonstrate its capability. Please refer to RGBD images for more available datasets. The Redwood dataset can be a good starting point.

If you use any part of the tensor-based reconstruction system or the hash map backend in Open3D, please cite [Dong2021]:

@article{Dong2021,
    author    = {Wei Dong, Yixing Lao, Michael Kaess, and Vladlen Koltun}
    title     = {{ASH}: A Modern Framework for Parallel Spatial Hashing in {3D} Perception},
    journal   = {arXiv:2110.00511},
    year      = {2021},
}

Note

As of now the tutorial is only for online dense SLAM, and offline integration with provided poses. The tutorials for tensor-based offline reconstruction system, Simultaneous localization and calibration (SLAC), and shape from shading (SfS) tutorials as mentioned in [Dong2021] are still under construction. At current, please refer to Reconstruction system for the legacy versions.