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Clustering Method of 3D Point Cloud of Muck-Pile Based on Connectivity of Adjacent Surface

Access Status
Open access
Authors
Shishido, H.
Wanzhi, Z.
Jang, Hyong Doo
Kawamura, Y.
Kameda, Y.
Kitahara, I.
Date
2019
Type
Conference Paper

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Citation
Shishido, H. and Wanzhi, Z. and Jang, H.D. and Kawamura, Y. and Kameda, Y. and Kitahara, I. 2019. Clustering Method of 3D Point Cloud of Muck-Pile Based on Connectivity of Adjacent Surface. In: 2019 IEEE 8th Global Conference on Consumer Electronics (GCCE 2019), 15th Oct 2019, OSAKA, Japan.
Source Conference
2019 IEEE 8th Global Conference on Consumer Electronics (GCCE 2019)
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Faculty
Faculty of Science and Engineering
School
WASM: Minerals, Energy and Chemical Engineering
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Abstract

This paper proposes a method to measure the fragmentation distribution of a pile of rocks (muck-pile) using image-based 3D reconstruction. One of the most important aspects of mine-blasting is appropriate rock fragmentation to optimize the cost of the blasting operation. The conventional method of measuring fragmentation distribution is based on 2D image processing including segmentation of muck-pile regions into rock clusters. However, in the 2D method, the measurement accuracy is limited. To accurately measure rock fragmentation distribution, we reconstructed a 3D model of a muck-pile from multi-view images and segment the 3D model based on rock-features such as color, normal vector, distance and adjacent angles of surface planes. As a result, the size of each rock was calculated by fitting a bounding box. Based on experimental evaluations, it was confirmed that the accuracy of the proposed method is higher than that of previous methods.