Enhanced Human Segmentation from 2D LiDAR Data Using DBSCAN Clustering

This study presents a comprehensive approach to segmenting human objects in point cloud data generated by 2D LiDAR sensors within indoor environments, where challenges such as shape variability, noise, and the presence of non-human objects complicate the process. The proposed method leverages the DB...

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Bibliographic Details

Published in:	2024 International Conference on Electrical and Information Technology (IEIT) pp. 33 - 37
Main Authors:	Fikri, Muhammad Ainul, Riansyah, Moch. Iskandar, Rahmanti, Farah Zakiyah
Format:	Conference Proceeding
Language:	English
Published:	IEEE 12.09.2024
Subjects:	2D LiDAR Accuracy Clustering algorithms DBSCAN Dynamics Heuristic algorithms Indoor environment Laser radar Noise Object recognition Point Cloud Data Segmentation Shape
Online Access:	Get full text
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