Matching Algorithm of 3D Point Clouds Based on Multiscale Features and Covariance Matrix Descriptors
The three-dimensional (3D) point cloud is one of the most promising tools for representing and identifying 3D objects. The critical step for matching is to find the appropriate feature descriptors. Two prevalent descriptors are global feature descriptor and local feature descriptor. The former repre...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2019-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/8846020/ |