• Journal of Internet Computing and Services
    ISSN 2287 - 1136 (Online) / ISSN 1598 - 0170 (Print)
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Improved Parameter Inference for Low-Cost 3D LiDAR-Based Object Detection on Clustering Algorithms


Da-hyeon Kim, Jun-ho Ahn, Journal of Internet Computing and Services, Vol. 23, No. 6, pp. 71-78, Dec. 2022
10.7472/jksii.2022.23.6.71, Full Text:
Keywords: 3D LiDAR, clustering, Object Detection, Fusion camera, Hyper-parameter

Abstract

This paper proposes an algorithm for 3D object detection by processing point cloud data of 3D LiDAR. Unlike 2D LiDAR, 3D LiDAR-based data was too vast and difficult to process in three dimensions. This paper introduces various studies based on 3D LiDAR and describes 3D LiDAR data processing. In this study, we propose a method of processing data of 3D LiDAR using clustering techniques for object detection and design an algorithm that fuses with cameras for clear and accurate 3D object detection. In addition, we study models for clustering 3D LiDAR-based data and study hyperparameter values according to models. When clustering 3D LiDAR-based data, the DBSCAN algorithm showed the most accurate results, and the hyperparameter values of DBSCAN were compared and analyzed. This study will be helpful for object detection research using 3D LiDAR in the future.


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Cite this article
[APA Style]
Kim, D. & Ahn, J. (2022). Improved Parameter Inference for Low-Cost 3D LiDAR-Based Object Detection on Clustering Algorithms. Journal of Internet Computing and Services, 23(6), 71-78. DOI: 10.7472/jksii.2022.23.6.71.

[IEEE Style]
D. Kim and J. Ahn, "Improved Parameter Inference for Low-Cost 3D LiDAR-Based Object Detection on Clustering Algorithms," Journal of Internet Computing and Services, vol. 23, no. 6, pp. 71-78, 2022. DOI: 10.7472/jksii.2022.23.6.71.

[ACM Style]
Da-hyeon Kim and Jun-ho Ahn. 2022. Improved Parameter Inference for Low-Cost 3D LiDAR-Based Object Detection on Clustering Algorithms. Journal of Internet Computing and Services, 23, 6, (2022), 71-78. DOI: 10.7472/jksii.2022.23.6.71.