# cilantro: A Lean, Versatile, and Efficient Library for Point Cloud Data Processing

arXiv: https://arxiv.org/abs/1807.00399 · HTML: https://mlsanity.com/paper/1807.00399/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 1 Jul 2018.

## Built on by (most cited first, 4 of 4)

- [A 5-Point Minimal Solver for Event Camera Relative Motion Estimation](https://mlsanity.com/paper/2309.17054/) (2023)
- [Continuous Event-Line Constraint for Closed-Form Velocity Initialization](https://mlsanity.com/paper/2109.04313/) (2021)
- [LiGuard: A Streamlined Open-Source Framework for Rapid & Interactive Lidar Research](https://mlsanity.com/paper/2509.02902/) (2025)
- [LECalib: Line-Based Event Camera Calibration](https://mlsanity.com/paper/2512.22441/) (2025)

## Abstract (arXiv)

We introduce cilantro, an open-source C++ library for geometric and general-purpose point cloud data processing. The library provides functionality that covers low-level point cloud operations, spatial reasoning, various methods for point cloud segmentation and generic data clustering, flexible algorithms for robust or local geometric alignment, model fitting, as well as powerful visualization tools. To accommodate all kinds of workflows, cilantro is almost fully templated, and most of its generic algorithms operate in arbitrary data dimension. At the same time, the library is easy to use and highly expressive, promoting a clean and concise coding style. cilantro is highly optimized, has a minimal set of external dependencies, and supports rapid development of performant point cloud processing software in a wide variety of contexts.