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Paper Abstract and Keywords
Presentation 2022-02-22 10:30
Interpolation Method for Sparse Point Cloud at Long-range Using Virtual RGB-D with LiDAR and Camera
Mai Saito, Shuncong Shen, Toshio Ito (SIT)
Abstract (in Japanese) (See Japanese page) 
(in English) LiDAR plays an important role in the external recognition due to its high spatial resolution for automated driving system. However, LiDAR has a problem that the point cloud data becomes sparse at long distances. This problem makes it difficult to obtain accurate information of the target object. To solve this problem, we propose an interpolation method using sensor fusion of camera and LiDAR. RGB data is used to search for matching point cloud in adjacent frames. In the experiment, the proposed method is applied to the data of a preceding vehicle, and the improvement of the accuracy of the shape recovery rate is confirmed.
Keyword (in Japanese) (See Japanese page) 
(in English) Autonomous vehicle / LiDAR / Sensor fusion / RGB-D / / / /  
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Conference Information
Committee AIT ME MMS IEICE-IE IEICE-ITS  
Conference Date 2022-02-21 - 2022-02-22 
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Place (in English) online 
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Paper Information
Registration To IEICE-ITS 
Conference Code 2022-02-IE-ITS-AIT-ME-MMS 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Interpolation Method for Sparse Point Cloud at Long-range Using Virtual RGB-D with LiDAR and Camera 
Sub Title (in English)  
Keyword(1) Autonomous vehicle  
Keyword(2) LiDAR  
Keyword(3) Sensor fusion  
Keyword(4) RGB-D  
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1st Author's Name Mai Saito  
1st Author's Affiliation Shibaura Institute of Technology (SIT)
2nd Author's Name Shuncong Shen  
2nd Author's Affiliation Shibaura Institute of Technology (SIT)
3rd Author's Name Toshio Ito  
3rd Author's Affiliation Shibaura Institute of Technology (SIT)
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Speaker Author-1 
Date Time 2022-02-22 10:30:00 
Presentation Time 15 minutes 
Registration for IEICE-ITS 
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Volume (vol) vol.46 
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