Novel CE-CBCE feature extraction method for object classification using a low-density LiDAR point cloud

Mohd Romlay, Muhammad Rabani and Mohd Ibrahim, Azhar and Toha, Siti Fauziah and De Wilde, Philippe and Venkat, Ibrahim (2021) Novel CE-CBCE feature extraction method for object classification using a low-density LiDAR point cloud. PLOS ONE, 16 (8). pp. 1-18. ISSN 1932-6203

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Abstract

Low-end LiDAR sensor provides an alternative for depth measurement and object recognition for lightweight devices. However due to low computing capacity, complicated algorithms are incompatible to be performed on the device, with sparse information further limits the feature available for extraction. Therefore, a classification method which could receive sparse input, while providing ample leverage for the classification process to accurately differentiate objects within limited computing capability is required. To achieve reliable feature extraction from a sparse LiDAR point cloud, this paper proposes a novel Clustered Extraction and Centroid Based Clustered Extraction Method (CE-CBCE) method for feature extraction followed by a convolutional neural network (CNN) object classifier. The integration of the CE-CBCE and CNN methods enable us to utilize lightweight actuated LiDAR input and provides low computing means of classification while maintaining accurate detection. Based on genuine LiDAR data, the final result shows reliable accuracy of 97% through the method proposed.

Item Type:	Article (Journal)
Additional Information:	This is collaborative work with Universiti Teknologi Brunei and University of Kent
Subjects:	T Technology > T Technology (General) T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK7800 Electronics. Computer engineering. Computer hardware. Photoelectronic devices T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK7800 Electronics. Computer engineering. Computer hardware. Photoelectronic devices > TK7885 Computer engineering
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button):	Kulliyyah of Engineering Kulliyyah of Engineering > Department of Mechatronics Engineering
Depositing User:	Dr Azhar Mohd Ibrahim
Date Deposited:	26 Aug 2021 09:16
Last Modified:	07 Sep 2021 10:33
URI:	http://irep.iium.edu.my/id/eprint/91744

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