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TIF-Reg: Point Cloud Registration with Transform-Invariant Features in SE(3)
| Content Provider | MDPI |
|---|---|
| Author | Chen, Baifan Chen, Hong Song, Baojun Gong, Grace |
| Copyright Year | 2021 |
| Abstract | Three-dimensional point cloud registration (PCReg) has a wide range of applications in computer vision, 3D reconstruction and medical fields. Although numerous advances have been achieved in the field of point cloud registration in recent years, large-scale rigid transformation is a problem that most algorithms still cannot effectively handle. To solve this problem, we propose a point cloud registration method based on learning and transform-invariant features (TIF-Reg). Our algorithm includes four modules, which are the transform-invariant feature extraction module, deep feature embedding module, corresponding point generation module and decoupled singular value decomposition (SVD) module. In the transform-invariant feature extraction module, we design TIF in SE(3) (which means the 3D rigid transformation space) which contains a triangular feature and local density feature for points. It fully exploits the transformation invariance of point clouds, making the algorithm highly robust to rigid transformation. The deep feature embedding module embeds TIF into a high-dimension space using a deep neural network, further improving the expression ability of features. The corresponding point cloud is generated using an attention mechanism in the corresponding point generation module, and the final transformation for registration is calculated in the decoupled SVD module. In an experiment, we first train and evaluate the TIF-Reg method on the ModelNet40 dataset. The results show that our method keeps the root mean squared error (RMSE) of rotation within 0.5 |
| Starting Page | 5778 |
| e-ISSN | 14248220 |
| DOI | 10.3390/s21175778 |
| Journal | Sensors |
| Issue Number | 17 |
| Volume Number | 21 |
| Language | English |
| Publisher | MDPI |
| Publisher Date | 2021-08-27 |
| Access Restriction | Open |
| Subject Keyword | Sensors Computation Theory and Mathematics Transform-invariant Feature Point Cloud Registration |
| Content Type | Text |
| Resource Type | Article |
