PPTFH: Robust Local Descriptor Based on Point-Pair Transformation Features for 3D Surface Matching
Three-dimensional feature description for a local surface is a core technology in 3D computer vision. Existing descriptors perform poorly in terms of distinctiveness and robustness owing to noise, mesh decimation, clutter, and occlusion in real scenes. In this paper, we propose a 3D local surface de...
Main Authors: | Lang Wu, Kai Zhong, Zhongwei Li, Ming Zhou, Hongbin Hu, Congjun Wang, Yusheng Shi |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2021-05-01
|
Series: | Sensors |
Subjects: | |
Online Access: | https://www.mdpi.com/1424-8220/21/9/3229 |
Similar Items
-
Performance Evaluation of 3D Descriptors Paired with Learned Keypoint Detectors
by: Riccardo Spezialetti, et al.
Published: (2021-05-01) -
Surface Area Distribution Descriptor for object matching
by: Mohamed F. Gafar, et al.
Published: (2010-07-01) -
Matching Algorithm of 3D Point Clouds Based on Multiscale Features and Covariance Matrix Descriptors
by: Bin Lu, et al.
Published: (2019-01-01) -
Matching Algorithm for 3D Point Cloud Recognition and Registration Based on Multi-Statistics Histogram Descriptors
by: Jinlong Li, et al.
Published: (2022-01-01) -
Fast Point Cloud Registration Algorithm Based on 3DNPFH Descriptor
by: Bo You, et al.
Published: (2022-06-01)