Novel 3D local feature descriptor of point clouds based on spatial voxel homogenization for feature matching

Visual Computing for Industry, Biomedicine, and Art

Original Article

Zhengyang Cai¹  Jiong Yang²  Dongyang Fang²  Jian Zhang² 

[1] School of Management, Hefei University of Technology, 230009, Hefei, Anhui, China;School of Mechanical and Power Engineering, Zhengzhou University, 450001, Zhengzhou, Henan, China;

关键词: Local feature descriptor;    Voxel;    Local reference frame;    Feature extraction;   

DOI  :  10.1186/s42492-023-00145-4

 received in 2023-05-16, accepted in 2023-09-14,  发布年份 2023

来源: Springer

【 摘 要 】

Obtaining a 3D feature description with high descriptiveness and robustness under complicated nuisances is a significant and challenging task in 3D feature matching. This paper proposes a novel feature description consisting of a stable local reference frame (LRF) and a feature descriptor based on local spatial voxels. First, an improved LRF was designed by incorporating distance weights into Z- and X-axis calculations. Subsequently, based on the LRF and voxel segmentation, a feature descriptor based on voxel homogenization was proposed. Moreover, uniform segmentation of cube voxels was performed, considering the eigenvalues of each voxel and its neighboring voxels, thereby enhancing the stability of the description. The performance of the descriptor was strictly tested and evaluated on three public datasets, which exhibited high descriptiveness, robustness, and superior performance compared with other current methods. Furthermore, the descriptor was applied to a 3D registration trial, and the results demonstrated the reliability of our approach.

【 授权许可】

CC BY   
© China Graphics Society 2023

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