韩国Yunjin Lee的博士论文，包含了她读博期间的主要研究成果，包括Mesh Scissoring: Contour-Based Segmentation，Mesh Parameterization Using Virtual Boundaries，Geometric Snakes for 3D Meshes，Mean Shift for 3D Meshes-Yunjin Lee Korean doctoral dissertation, including during her读博the

Mean Shift算法的基本原理，着重研究了Mean Shift的迭代过程和收敛性以及特征空间的结构。通过Mean Shift结构分析，本章提出了一种快速区域合并算法并将其应用于改进的Mean Shift图像分割算法。-The basic principle of the Mean Shift algorithm, focusing on the Mean Shift iteration process and convergence and the structure of the feat

mean shift 算法聚类和分割，可以用来处理图像-mean shift algorithm clustering and segmentation, can be used to deal with image

集成改进Mean Shift 和区域合并两种算法的图像分割,能得到更好的分割效果，且能在一定程度上提高遥感影像分割的自动化。-Improved Mean Shift and regional integration merge two algorithms for image segmentation, segmentation can get better results, and can improve the automation of remote sensing image segme