基于(μ+λ)演化策略的超二次曲面三维建模与分割

(μ+λ) Evolutionary Strategy for 3D Modeling and Segmentation with Superquadrics

针对离散不规则数据点的三维建模与分割,用超二次曲面参数模型作为初始化种子,结合(μ+λ)演化策略来产生最佳初始化播种状态,采用最近邻方案对最佳初始化种子进行合并与分割.实验结果表明,该方法既产生了较好的建模与分割效果,又得到物体各部分之间的拓扑关系,可作为物体识别的重要依据.

For the discrete proposed. By using the supe and irregular data points, a new method of 3D modeling and segmentation was rquadric parametric models as initial seeds, the best initial seeding state was obtained based on the （μ＋λ） evolutionary strategy, then the nearest neighboring approach was utilized for efficient merging and segmentation of those best initial seeds. Experimental results show that the proposed method can not only achieve the effective modeling and segmentation, but also obtain the topologic relation among the object parts, which is useful for recognition of 3D objects.