Semi-Dense Point Clouds (background)

1 Semi-Dense Point Clouds

Project Aria’s documentation and LSD-SLAM literature describe semi-dense tracks, inverse-distance parameterization, and world-frame points [1]. This compact page preserves that external background only.

ARIA-NBV’s geometry, notation, data shape, and validation are owned by the Typst thesis plus the relevant Python docstrings/tests. For neighboring background see ASE and EFM3D embeddings.

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References

[1]
J. Engel, T. Schöps, and D. Cremers, “LSD-SLAM: Large-scale direct monocular SLAM,” in Computer vision – ECCV 2014, in Lecture notes in computer science, vol. 8690. Cham: Springer, 2014, pp. 834–849. doi: 10.1007/978-3-319-10605-2_54.