点云
转化(遗传学)
钥匙(锁)
计算机科学
变换矩阵
刚性变换
几何变换
人工智能
点(几何)
基质(化学分析)
图像(数学)
云计算
计算机视觉
算法
数学
几何学
基因
操作系统
经典力学
物理
生物化学
运动学
计算机安全
复合材料
化学
材料科学
作者
Hui Chen,Dongge Sun,Wanquan Liu,Haiyuan Wu,Man Liang,Peter Liu
出处
期刊:IEEE Transactions on Geoscience and Remote Sensing
[Institute of Electrical and Electronics Engineers]
日期:2022-01-01
卷期号:60: 1-15
标识
DOI:10.1109/tgrs.2022.3175758
摘要
Most traditional methods for extracting key points from the 3D point cloud are based on the geometric features of points and they pose problems such as low accuracy. In order to solve these problems, this paper proposes a novel approach based on 2D image mapping, making it able to achieve highly accurate localization of key points. Specifically, it works as follows: input images are first selected for Harris corner detection; the three pairs of marker points of the images and the point cloud are then selected to calculate the transformation matrix T between them; next, the image key points are mapped onto the three-dimensional points through the transformation matrix T, for which the extraction of key points is achieved. Experimental results show that the proposed algorithm is able to greatly improve the extraction accuracy of key points in comparison with traditional algorithms.
科研通智能强力驱动
Strongly Powered by AbleSci AI