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3D object detection-based vehicle localiazation system for bus stations
Huang Xingbin,Wen Zhigang *
School of Electronic Engineering, Beijing University of Posts and Telecommunications, 100876;School of Electronic Engineering, Beijing University of Posts and Telecommunications, 100876
*Correspondence author
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Funding: none
Opened online:10 March 2022
Accepted by: none
Citation: Huang Xingbin,Wen Zhigang.3D object detection-based vehicle localiazation system for bus stations[OL]. [10 March 2022] http://en.paper.edu.cn/en_releasepaper/content/4756382
 
 
Now vehicle location technology is more and more widely used in people\'s lives. 3D object detection methods based on LiDAR sensors have achieved success in detection accuracy, but LiDAR sensors are too expensive to be widely used. The methods using images for 3D object detection reduce the cost, but often have poor performance because of the lack of depth information. In this paper, we propose a 3D object detection framework named Depth-Guided and Depth-Aware (DGDA) which is able to simultaneously utilize perspective information of RGB images and depth information of depth maps for 3D detection. Experiments on the KITTI dataset show that DGDA outperforms the most existing image-based 3D object detection algorithms. It is worth mentioning that traditional image-based 3D object detection techniques are only used for the images captured from a driving perspective. In order to apply the 3D detection technology to the vehicle localization of the surveillance video of the bus station, we also propose an angle conversion localization algorithm and combine it with the DGDA framework to design an end-to-end vehicle location system for bus station.
Keywords:computer vision; vehicle localization; 3D object detection; RGB image; depth map; angle conversion localization algorithm;
 
 
 

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