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Fast Concave Hull

This is a fast implementation of concave hull using a k-nearest neighbour approach.

Concave Hull Approximation of Hessigheim Benchmark

Concave Hull on LiDAR Point Cloud Data with over 1M points. The calculation took 2.88 seconds to run.

Implementation Details

The current implementation is based on the paper

Moreira, A., & Santos, M. Y. (2007). Concave hull: A k-nearest neighbours approach for the computation of the region occupied by a set of points.

The algorithm has a parameter $k$, the number of neighbors, and controls the "smoothness" of the hull.

Setup Rust

Use Cargo

cargo build

Setup Python (Development)

Use PyO3 + Maturin

maturin develop