Robust and accurate depth estimation by fusing LiDAR and stereo
文献类型：期刊论文
| 作者 | Xu, Guangyao1 ; Cao, Xuewei1; Liu, Jiaxin2; Fan, Junfeng1; Li, En1; Long, Xiaoyu1
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| 刊名 | MEASUREMENT SCIENCE AND TECHNOLOGY
 |
| 出版日期 | 2023-12-01 |
| 卷号 | 34期号:12页码:11 |
| 关键词 | stereo matching LiDAR depth estimation multi-sensor fusion up-sampling |
| ISSN号 | 0957-0233 |
| DOI | 10.1088/1361-6501/acef47 |
| 通讯作者 | Li, En(en.li@ia.ac.cn) |
| 英文摘要 | Depth estimation is one of the key technologies in some fields such as autonomous driving and robot navigation. However, the traditional method of using a single sensor is inevitably limited by the sensor's performance. Therefore, a precise and robust method for fusing LiDAR and stereo cameras is proposed. This method fully combines the advantages of the LiDAR and stereo cameras, which can retain the advantages of the high precision of the LiDAR and the high resolution of images respectively. Compared with the traditional stereo matching method, the texture of the object and lighting conditions have less influence on the algorithm. Firstly, the depth of the LiDAR data is converted to the disparity of the stereo camera. Because the density of the LiDAR data is relatively sparse on the y-axis, the converted disparity map is up-sampled using the interpolation method. Secondly, in order to make full use of the precise disparity map, the disparity map and stereo-matching are fused to propagate the accurate disparity. Finally, the disparity map is converted to the depth map. Moreover, the converted disparity map can also increase the speed of the algorithm. We evaluate the proposed pipeline on the KITTI benchmark. The experiment demonstrates that our algorithm has higher accuracy than several classic methods. |
| WOS关键词 | NETWORK |
| 资助项目 | National Natural Science Foundation of China[62273344] ; National Natural Science Foundation of China[61973300] |
| WOS研究方向 | Engineering ; Instruments & Instrumentation |
| 语种 | 英语 |
| WOS记录号 | WOS:001051857900001 |
| 出版者 | IOP Publishing Ltd |
| 资助机构 | National Natural Science Foundation of China |
| 源URL | [http://ir.ia.ac.cn/handle/173211/54011]  |
| 专题 | 复杂系统认知与决策实验室 中科院工业视觉智能装备工程实验室 |
| 通讯作者 | Li, En |
| 作者单位 | 1.Chinese Acad Sci, Inst Automat, Beijing 100000, Peoples R China 2.State Grid Liaoning Elect Power Co Ltd, Shenyang 110000, Peoples R China |
| 推荐引用方式 GB/T 7714 | Xu, Guangyao,Cao, Xuewei,Liu, Jiaxin,et al. Robust and accurate depth estimation by fusing LiDAR and stereo[J]. MEASUREMENT SCIENCE AND TECHNOLOGY,2023,34(12):11. |
| APA | Xu, Guangyao,Cao, Xuewei,Liu, Jiaxin,Fan, Junfeng,Li, En,&Long, Xiaoyu.(2023).Robust and accurate depth estimation by fusing LiDAR and stereo.MEASUREMENT SCIENCE AND TECHNOLOGY,34(12),11. |
| MLA | Xu, Guangyao,et al."Robust and accurate depth estimation by fusing LiDAR and stereo".MEASUREMENT SCIENCE AND TECHNOLOGY 34.12(2023):11. |
入库方式： OAI收割
来源：自动化研究所
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