粒子群优化算法的三维可视化最佳视点选取（英文）

发布时间：2018-06-01 12:37

  本文选题：三维可视化 + 视点选取　； 参考：《系统仿真学报》2017年10期

【摘要】：视点选取为了提供给用户较好的观察位置,涉及到视点质量好坏的评估。提出了粒子群优化算法的三维可视化最佳视点选取方法。通过采用图像信息熵与图像边缘熵进行视点质量的评估,通过多目标智能优化方法选取视点。基本流程是由初始视点集开始,通过编码、粒子评价和粒子更新等操作寻找最佳视点,这是一个多次迭代的过程,直至找到满意的视点或者达到迭代最大代数。实验表明,该方法可行有效,能自动完成最佳视点的选取,有效地减少了人工试探选取次数。
[Abstract]:The viewpoint selection is to provide the user with better observation position, which involves the evaluation of the quality of the view. A method of selecting the best viewpoint of 3D visualization based on particle swarm optimization (PSO) is proposed. Image information entropy and image edge entropy are used to evaluate the quality of view point, and multi-objective intelligent optimization method is used to select the view point. The basic process is to start with the initial viewpoint set and to find the best viewpoint by coding, particle evaluation and particle updating. This is a multi-iteration process until satisfactory viewpoint is found or the iterative maximum algebra is reached. The experimental results show that the method is feasible and effective, which can automatically select the best viewpoint and reduce the number of manual heuristics.
【作者单位】： 河南理工大学计算机科学与技术学院;
【基金】：National Natural Science Foundation of China(61503124)
【分类号】：TP18;TP391.41
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本文编号：1964207