摘要
主要讨论了基于序列图像的三维重建中的两个关键算法:特征数据点列的重采样算法与三角化算法.本文改进了Chetverikov等提出的轮廓曲线中高曲率点的检测算法,使在重采样时,数据的压缩比得到了明显的改善,也显著地提高了可视化速度.并使用一种简单的三角化算法,对重采样后的数据点列进行三角化,实现目标的三维重建.
Two important algorithm in 3D reconstruction of image sequences are studied, i.e. re-sampling algorithm and triangulation algorithm. An improved algorithm for detection of high curvature points in planar curves is presented. This algorithm can improve the performance of re-sampling and 3D data field visualization. Triangulation is implemented by using a simple triangulation algorithm. Sequentially, 3D object reconstruction was achieved.
出处
《湖南理工学院学报（自然科学版）》
CAS
2010年第1期35-38,共4页
Journal of Hunan Institute of Science and Technology(Natural Sciences)
关键词
图像序列
三维重建
高曲率
重采样
三角化
image sequence
3D reconstruction
High Curvature
re-sampling
triangulation
