PDE-Based Medial Axis Extraction and Shape Manipulation of Arbitrary Meshes

Shape skeletonization （i.e., medial axis extraction） is powerful in many visual computing applications, such as pattern recognition, object segmentation, registration, and animation. In this paper, the authors expand the use of diffusion equations combined with distance field information to approximate medial axes of arbitrary 3D differential properties. It offers an alternative solids represented by polygonal meshes based on their but natural way for medial axis extraction for commonly used 3D polygonal models. By solving the PDE along time axis, this system can not only quickly extract diffusion-based medial axes of input meshes, but also allow users to visualize the extraction process at each time step. In addition, the proposed model provides users a set of manipulation toolkits to sculpt extracted medial axes, then use diffusion-based techniques to recover corresponding deformed shapes according to the original input datasets. This skeleton-based shape manipulation offers a fast and easy way for animation and deformation of complicated mesh objects.     

空间调制系统的星座优化设计

作为一种新颖的多天线技术,空间调制(spatial modulation, SM)受到了学者的关注。近年来,SM系统的星座设计成为研究热点。然而现有的星座设计算法由于预先设定星座结构,导致不能得到最优的星座图。对此,在发送功率受限的条件下提出一种新的星座设计方案。该方案基于最小化SM系统误符号率(symbol error rate, SER)准则,通过扩大可行域范围并利用遗传算法，对SM系统的信号星座进行了优化。此外,深入分析了信号星座对SER及系统参数对星座设计的影响。仿真结果表明,该算法得到的星座图相比于其他星座图具有更好的SER性能。