High-Accuracy Globally Consistent Surface Reconstruction Using Fringe Projection Profilometry
This paper presents a high-accuracy method for globally consistent surface reconstruction using a single fringe projection profilometry (FPP) sensor. To solve the accumulated sensor pose estimation error problem encountered in a long scanning trajectory, we first present a novel 3D registration meth...
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| Format: | Article |
| Language: | English |
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MDPI AG
2019-02-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/19/3/668 |
| _version_ | 1797999276762071040 |
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| author | Xu Cheng Xingjian Liu Zhongwei Li Kai Zhong Liya Han Wantao He Wanbing Gan Guoqing Xi Congjun Wang Yusheng Shi |
| author_facet | Xu Cheng Xingjian Liu Zhongwei Li Kai Zhong Liya Han Wantao He Wanbing Gan Guoqing Xi Congjun Wang Yusheng Shi |
| author_sort | Xu Cheng |
| collection | DOAJ |
| description | This paper presents a high-accuracy method for globally consistent surface reconstruction using a single fringe projection profilometry (FPP) sensor. To solve the accumulated sensor pose estimation error problem encountered in a long scanning trajectory, we first present a novel 3D registration method which fuses both dense geometric and curvature consistency constraints to improve the accuracy of relative sensor pose estimation. Then we perform global sensor pose optimization by modeling the surface consistency information as a pre-computed covariance matrix and formulating the multi-view point cloud registration problem in a pose graph optimization framework. Experiments on reconstructing a 1300 mm × 400 mm workpiece with a FPP sensor is performed, verifying that our method can substantially reduce the accumulated error and achieve industrial-level surface model reconstruction without any external positional assistance but only using a single FPP sensor. |
| first_indexed | 2024-04-11T11:02:05Z |
| format | Article |
| id | doaj.art-9230ed8e3101488b9fd0075aae798cb2 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-11T11:02:05Z |
| publishDate | 2019-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-9230ed8e3101488b9fd0075aae798cb22022-12-22T04:28:30ZengMDPI AGSensors1424-82202019-02-0119366810.3390/s19030668s19030668High-Accuracy Globally Consistent Surface Reconstruction Using Fringe Projection ProfilometryXu Cheng0Xingjian Liu1Zhongwei Li2Kai Zhong3Liya Han4Wantao He5Wanbing Gan6Guoqing Xi7Congjun Wang8Yusheng Shi9State Key Laboratory of Material Processing and Die & Mould Technology, Huazhong University of Science and Technology, Wuhan 430074, ChinaState Key Laboratory of Material Processing and Die & Mould Technology, Huazhong University of Science and Technology, Wuhan 430074, ChinaState Key Laboratory of Material Processing and Die & Mould Technology, Huazhong University of Science and Technology, Wuhan 430074, ChinaState Key Laboratory of Material Processing and Die & Mould Technology, Huazhong University of Science and Technology, Wuhan 430074, ChinaState Key Laboratory of Material Processing and Die & Mould Technology, Huazhong University of Science and Technology, Wuhan 430074, ChinaSchool of Mechanical Engineering, Heilongjiang University of Science and Technology, Harbin 150022, ChinaHubei Tri-Ring Forging Co., Ltd, Gucheng 441700, ChinaHubei Tri-Ring Forging Co., Ltd, Gucheng 441700, ChinaState Key Laboratory of Material Processing and Die & Mould Technology, Huazhong University of Science and Technology, Wuhan 430074, ChinaState Key Laboratory of Material Processing and Die & Mould Technology, Huazhong University of Science and Technology, Wuhan 430074, ChinaThis paper presents a high-accuracy method for globally consistent surface reconstruction using a single fringe projection profilometry (FPP) sensor. To solve the accumulated sensor pose estimation error problem encountered in a long scanning trajectory, we first present a novel 3D registration method which fuses both dense geometric and curvature consistency constraints to improve the accuracy of relative sensor pose estimation. Then we perform global sensor pose optimization by modeling the surface consistency information as a pre-computed covariance matrix and formulating the multi-view point cloud registration problem in a pose graph optimization framework. Experiments on reconstructing a 1300 mm × 400 mm workpiece with a FPP sensor is performed, verifying that our method can substantially reduce the accumulated error and achieve industrial-level surface model reconstruction without any external positional assistance but only using a single FPP sensor.https://www.mdpi.com/1424-8220/19/3/668quality controlfringe projection profilometrydepth image registration3D reconstruction |
| spellingShingle | Xu Cheng Xingjian Liu Zhongwei Li Kai Zhong Liya Han Wantao He Wanbing Gan Guoqing Xi Congjun Wang Yusheng Shi High-Accuracy Globally Consistent Surface Reconstruction Using Fringe Projection Profilometry Sensors quality control fringe projection profilometry depth image registration 3D reconstruction |
| title | High-Accuracy Globally Consistent Surface Reconstruction Using Fringe Projection Profilometry |
| title_full | High-Accuracy Globally Consistent Surface Reconstruction Using Fringe Projection Profilometry |
| title_fullStr | High-Accuracy Globally Consistent Surface Reconstruction Using Fringe Projection Profilometry |
| title_full_unstemmed | High-Accuracy Globally Consistent Surface Reconstruction Using Fringe Projection Profilometry |
| title_short | High-Accuracy Globally Consistent Surface Reconstruction Using Fringe Projection Profilometry |
| title_sort | high accuracy globally consistent surface reconstruction using fringe projection profilometry |
| topic | quality control fringe projection profilometry depth image registration 3D reconstruction |
| url | https://www.mdpi.com/1424-8220/19/3/668 |
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