A 3D Tracking and Registration Method Based on Point Cloud and Visual Features for Augmented Reality Aided Assembly System
To improve the robustness and applicability of 3D tracking and registration for augmented reality(AR) aided mechanical assembly system, a 3D registration and tracking method based on the point cloud and visual features is proposed. Firstly, the reference model point cloud is used to definite absolut...
| Format: | Article |
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| Language: | zho |
| Published: |
EDP Sciences
2019-02-01
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| Series: | Xibei Gongye Daxue Xuebao |
| Subjects: | |
| Online Access: | https://www.jnwpu.org/articles/jnwpu/full_html/2019/01/jnwpu2019371p143/jnwpu2019371p143.html |
| _version_ | 1797427476676214784 |
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| collection | DOAJ |
| description | To improve the robustness and applicability of 3D tracking and registration for augmented reality(AR) aided mechanical assembly system, a 3D registration and tracking method based on the point cloud and visual features is proposed. Firstly, the reference model point cloud is used to definite absolute tracking coordinate system, thus the locating datum of the virtual assembly guidance information is determined. Then by adding visual features matching to the iterative closest points (ICP) registration process, the robustness of tracking and registration is improved. In order to obtain sufficient number of visual feature matching points in this process, a visual feature matching strategy based on orientation vector consistency is proposed. Finally, the loop closure detection and global pose optimization from key frames are added in the tracking registration process. The experimental result shows that the proposed method has good real-time performance and accuracy, and the running speed can reach 30 frames per second. Moreover, it also shows good robustness when the camera is moving fast and the depth information is inaccurate, and the comprehensive performance of the proposed method is better than the KinectFusion method. |
| first_indexed | 2024-03-09T08:45:34Z |
| format | Article |
| id | doaj.art-1de8678f9ea34f1b8bd46b735be0758c |
| institution | Directory Open Access Journal |
| issn | 1000-2758 2609-7125 |
| language | zho |
| last_indexed | 2024-03-09T08:45:34Z |
| publishDate | 2019-02-01 |
| publisher | EDP Sciences |
| record_format | Article |
| series | Xibei Gongye Daxue Xuebao |
| spelling | doaj.art-1de8678f9ea34f1b8bd46b735be0758c2023-12-02T15:31:36ZzhoEDP SciencesXibei Gongye Daxue Xuebao1000-27582609-71252019-02-0137114315110.1051/jnwpu/20193710143jnwpu2019371p143A 3D Tracking and Registration Method Based on Point Cloud and Visual Features for Augmented Reality Aided Assembly System012School of Mechanical Engineering, Northwestern Polytechnical UniversitySchool of Mechanical Engineering, Northwestern Polytechnical UniversitySchool of Mechanical Engineering, Northwestern Polytechnical UniversityTo improve the robustness and applicability of 3D tracking and registration for augmented reality(AR) aided mechanical assembly system, a 3D registration and tracking method based on the point cloud and visual features is proposed. Firstly, the reference model point cloud is used to definite absolute tracking coordinate system, thus the locating datum of the virtual assembly guidance information is determined. Then by adding visual features matching to the iterative closest points (ICP) registration process, the robustness of tracking and registration is improved. In order to obtain sufficient number of visual feature matching points in this process, a visual feature matching strategy based on orientation vector consistency is proposed. Finally, the loop closure detection and global pose optimization from key frames are added in the tracking registration process. The experimental result shows that the proposed method has good real-time performance and accuracy, and the running speed can reach 30 frames per second. Moreover, it also shows good robustness when the camera is moving fast and the depth information is inaccurate, and the comprehensive performance of the proposed method is better than the KinectFusion method.https://www.jnwpu.org/articles/jnwpu/full_html/2019/01/jnwpu2019371p143/jnwpu2019371p143.htmlaugmented realitymechanical assembly3d registration and trackingpoint cloudvisual featurerobustnessvisual feature matchingloop closure detectionglobal pose optimization |
| spellingShingle | A 3D Tracking and Registration Method Based on Point Cloud and Visual Features for Augmented Reality Aided Assembly System Xibei Gongye Daxue Xuebao augmented reality mechanical assembly 3d registration and tracking point cloud visual feature robustness visual feature matching loop closure detection global pose optimization |
| title | A 3D Tracking and Registration Method Based on Point Cloud and Visual Features for Augmented Reality Aided Assembly System |
| title_full | A 3D Tracking and Registration Method Based on Point Cloud and Visual Features for Augmented Reality Aided Assembly System |
| title_fullStr | A 3D Tracking and Registration Method Based on Point Cloud and Visual Features for Augmented Reality Aided Assembly System |
| title_full_unstemmed | A 3D Tracking and Registration Method Based on Point Cloud and Visual Features for Augmented Reality Aided Assembly System |
| title_short | A 3D Tracking and Registration Method Based on Point Cloud and Visual Features for Augmented Reality Aided Assembly System |
| title_sort | 3d tracking and registration method based on point cloud and visual features for augmented reality aided assembly system |
| topic | augmented reality mechanical assembly 3d registration and tracking point cloud visual feature robustness visual feature matching loop closure detection global pose optimization |
| url | https://www.jnwpu.org/articles/jnwpu/full_html/2019/01/jnwpu2019371p143/jnwpu2019371p143.html |