Linear time DBSCAN for sorted 1D data and laser range scan segmentation
arXiv:2103.16245v12 citations
Originality Synthesis-oriented
AI Analysis
This is an incremental improvement for robotics and computer vision applications using laser range scans.
The paper tackled line extraction from laser range data by casting it as 1D problems and proposing a fast DBSCAN specialization, achieving suitability for real-time applications with good noise handling.
This paper introduces new algorithm for line extraction from laser range data including methodology for efficient computation. The task is cast to series of one dimensional problems in various spaces. A fast and simple specialization of DBSCAN algorithm is proposed to solve one dimensional subproblems. Experiments suggest that the method is suitable for real-time applications, handles noise well and may be useful in practice.