發(fā)布時(shí)間：2018-06-01 12:37

  本文選題：三維可視化 + 視點(diǎn)選取　； 參考：《系統(tǒng)仿真學(xué)報(bào)》2017年10期

【摘要】：視點(diǎn)選取為了提供給用戶較好的觀察位置,涉及到視點(diǎn)質(zhì)量好壞的評估。提出了粒子群優(yōu)化算法的三維可視化最佳視點(diǎn)選取方法。通過采用圖像信息熵與圖像邊緣熵進(jìn)行視點(diǎn)質(zhì)量的評估,通過多目標(biāo)智能優(yōu)化方法選取視點(diǎn)。基本流程是由初始視點(diǎn)集開始,通過編碼、粒子評價(jià)和粒子更新等操作尋找最佳視點(diǎn),這是一個(gè)多次迭代的過程,直至找到滿意的視點(diǎn)或者達(dá)到迭代最大代數(shù)。實(shí)驗(yàn)表明,該方法可行有效,能自動(dòng)完成最佳視點(diǎn)的選取,有效地減少了人工試探選取次數(shù)。
[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.
【作者單位】： 河南理工大學(xué)計(jì)算機(jī)科學(xué)與技術(shù)學(xué)院;
【基金】：National Natural Science Foundation of China(61503124)
【分類號】：TP18;TP391.41
，

本文編號：1964207