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Journal Articles

Discrimination of the structures in nuclear facility station by deep learning based on 3D point cloud data

Imabuchi, Takashi; Tanifuji, Yuta; Kawabata, Kuniaki

Proceedings of 2022 IEEE/SICE International Symposium on System Integration (SII 2022) (Internet), p.1036 - 1040, 2022/01

This paper describes a method for discrimination of the structures in nuclear power station by deep learning based on 3D point cloud data. In order to promote safe and steady decommissioning work, it is important to estimate and assume the condition in nuclear power station based on the measured sensor data. Especially, the data of the dose rate in the workspace is useful to plan the decommissioning task and, the shape and the material property of the structures in the workspace are required for the dose rate simulation. Shape data can be obtained by such as 3D Scan, however, it is difficult to acquire the material property data of the objects. Therefore, we consider that it is possible that the major material property can be estimated from the category of the structures in nuclear power station. In this paper, we proposed a structure discrimination method by 3D semantic segmentation with 3D point cloud data that consists of labeled points by referring category labels of CAD data of existing nuclear facility. We reported discrimination performance of the proposed method by hold-out validation.

Journal Articles

Image selection method from image sequence to improve computational efficiency of 3D reconstruction; Analysis of inter-image displacement based on optical flow for evaluating 3D reconstruction performance

Hanari, Toshihide; Kawabata, Kuniaki; Nakamura, Keita

Proceedings of 2022 IEEE/SICE International Symposium on System Integration (SII 2022) (Internet), p.1041 - 1045, 2022/01

 Times Cited Count:0 Percentile:0.54

This paper describes the image selection method for an efficient three-dimensional (3D) reconstruction computation from an image sequence. Adequate images must be selected from the image sequence to improve the computational efficiency of the 3D reconstruction. Thus, we investigated a threshold based on the displacement among images obtained from a camera mounted on a remotely operated robot. The results confirmed that the proposed method can select adequate images for efficient 3D reconstruction by the threshold based on the optical flow from the image sequence. Therefore, the computational cost could be reduced by eliminating the duplicate and high-similarity images to perform the efficient 3D reconstruction.

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