本文關(guān)鍵詞： 計算機圖形學(xué) 三維卡通人臉 流形學(xué)習(xí) 主成分分析　出處：《湘潭大學(xué)》2009年碩士論文　論文類型：學(xué)位論文

【摘要】： 在信息技術(shù)迅猛發(fā)展的今天,數(shù)字娛樂已融入到人們生活的各個角落。近年來,卡通產(chǎn)品受到了社會各年齡階層人群的青睞。隨著三維虛擬環(huán)境技術(shù)的發(fā)展和普遍應(yīng)用,三維卡通形象在動漫影視、在線游戲、虛擬社區(qū)、輔助教學(xué)等領(lǐng)域呈現(xiàn)出越來越廣泛的應(yīng)用。目前,傳統(tǒng)的手工制作方法和基于規(guī)則生成的方法都無法解決實際應(yīng)用中實時性、藝術(shù)背景相關(guān)性、制作成本過大等問題。本文采用流形學(xué)習(xí)、主成分分析等方法對三維卡通人臉生成的問題展開研究,取得了如下的研究成果: 首先本文建立了一個由二維卡通人臉圖片、三維卡通人臉模型組成的卡通樣本庫,進(jìn)一步地,本文對三維人臉部件給出了定義,從而相應(yīng)地也構(gòu)建出了三維卡通人臉部件樣本庫。 其次,本文應(yīng)用局部線性嵌入的降維方法來獲得樣本庫中二維卡通和三維卡通人臉的低維嵌入,然后再應(yīng)用半監(jiān)督流形學(xué)習(xí)的方法挖掘出二維卡通數(shù)據(jù)集與三維卡通人臉數(shù)據(jù)集之間的映射關(guān)系,將此映射關(guān)系應(yīng)用于二維卡通來獲得與之對應(yīng)的三維卡通人臉的低維嵌入,再通過局部線性嵌入的升維方法重構(gòu)出其相應(yīng)的三維卡通人臉,從而擴(kuò)充三維卡通人臉樣本庫。 最后本文基于擴(kuò)充的三維卡通人臉樣本庫,采用主成分分析的方法實現(xiàn)了個性化的三維卡通人臉生成。
[Abstract]:With the rapid development of information technology, digital entertainment has been integrated into every corner of people's life. In recent years, cartoon products have been favored by people of all ages. The 3D cartoon image has been used more and more widely in the fields of animation, film and television, online game, virtual community, assistant teaching and so on. At present, the traditional manual production method and the rule based method can not solve the real time problem in the practical application. In this paper, manifold learning and principal component analysis are used to study the problem of 3D cartoon face generation, and the following research results are obtained:. First of all, a cartoon sample library composed of 2D cartoon face images and 3D cartoon face models is established. Furthermore, the definition of 3D face components is given in this paper. Accordingly, a 3D cartoon face sample library is constructed. Secondly, the method of local linear embedding is used to obtain the low dimensional embedding of 2D cartoon and 3D cartoon face in the sample database. Then the mapping relationship between 2D cartoon data set and 3D cartoon face data set is mined by semi-supervised manifold learning method, and the mapping relation is applied to two-dimensional cartoon to obtain the low-dimensional embedding of the corresponding 3D cartoon face. Then the corresponding 3D cartoon face is reconstructed by the method of local linear embedding, and the 3D cartoon face sample database is expanded. Finally, based on the expanded 3D cartoon face sample database, the method of principal component analysis (PCA) is used to realize personalized 3D cartoon face generation.
【學(xué)位授予單位】：湘潭大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2009
【分類號】：TP391.41

【引證文獻(xiàn)】

相關(guān)碩士學(xué)位論文 前1條

1 塔依爾.阿力甫;單側(cè)唇裂修復(fù)術(shù)下三角瓣法虛擬手術(shù)平臺的初步建立[D];新疆醫(yī)科大學(xué);2012年

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本文編號：1511569