Real-time ground filtering algorithm of cloud points acquired using Terrestrial Laser Scanner (TLS)

TL;DR

This paper introduces two real-time ground filtering algorithms for terrestrial laser scanner point clouds, demonstrating that the voxel-based method outperforms the normal vector approach in speed and accuracy.

Contribution

The study compares two novel ground filtering algorithms for TLS data, highlighting the superior performance of the voxel-based method in real-time applications.

Findings

Voxel-based algorithm is faster and more effective

Normal vector method is less efficient

Voxel method improves real-time ground filtering

Abstract

3D modeling based on point clouds requires ground-filtering algorithms that separate ground from non-ground objects. This study presents two ground filtering algorithms. The first one is based on normal vectors. It has two variants depending on the procedure to compute the k-nearest neighbors. The second algorithm is based on transforming the cloud points into a voxel structure. To evaluate them, the two algorithms are compared according to their execution time, effectiveness and efficiency. Results show that the ground filtering algorithm based on the voxel structure is faster in terms of execution time, effectiveness, and efficiency than the normal vector ground filtering.