本文選題：主動(dòng)表觀模型　切入點(diǎn)：人臉卡通化　出處：《電子科技大學(xué)》2013年碩士論文　論文類型：學(xué)位論文

【摘要】：人臉的多樣性和獨(dú)特性一直是計(jì)算機(jī)視覺、圖形學(xué)和模式識(shí)別等領(lǐng)域研究的熱點(diǎn)問題；卡通化藝術(shù)以其特有的表現(xiàn)形式和手法引領(lǐng)著藝術(shù)發(fā)展的新潮流；兩者相結(jié)合的人臉卡通化通過線條的描繪和顏色的渲染，以其特有的夸張模式，形象和逼真的再現(xiàn)人臉圖像，在網(wǎng)絡(luò)游戲、互動(dòng)論壇、社交軟件以及動(dòng)漫等領(lǐng)域應(yīng)用廣泛。 現(xiàn)有的基于學(xué)習(xí)的人臉卡通化方法通常將圖像分成若干小塊，，并通過對(duì)圖像塊的匹配及合成，來實(shí)現(xiàn)卡通圖像的合成。然而受到塊效應(yīng)的影響，圖像中的人臉特征細(xì)節(jié)描述不詳細(xì)，人臉線條效果欠佳。而目前流行的人臉定位方法，通過對(duì)人臉特征的準(zhǔn)確定位，能夠得到更好的細(xì)節(jié)描述及線條效果。 本文主要研究對(duì)于一幅給定的人臉圖像計(jì)算機(jī)如何自動(dòng)地生成具藝術(shù)家繪畫作品特定風(fēng)格的卡通人臉圖像，以及對(duì)卡通人臉進(jìn)行表情動(dòng)畫變換。主要的研究?jī)?nèi)容如下： 一、提出了兩種基于學(xué)習(xí)的卡通人臉圖像生成算法：基于參數(shù)模型的卡通化方法和基于特征點(diǎn)的卡通化方法�；趨�(shù)模型的卡通化方法是在主動(dòng)表觀模型的基礎(chǔ)上，通過學(xué)習(xí)人臉匹配的過程，利用參數(shù)估計(jì)的方法生成卡通人臉圖像；基于特征點(diǎn)的卡通化方法則從高層語義學(xué)的角度出發(fā)，將人臉特征分類處理，通過分別合成卡通人臉頭發(fā)、輪廓和五官，實(shí)現(xiàn)卡通人臉圖像的生成。 二、為了得到較好的彩色卡通效果，采用三種顏色渲染方法對(duì)卡通圖像上色，分別為基于顏色空間轉(zhuǎn)換的方法和基于圖像分割的方法�；陬伾臻g轉(zhuǎn)換的著色方法得到的卡通圖像色調(diào)與輸入圖像相似，而基于圖像分割的著色方法得到卡通圖像與藝術(shù)家繪畫的色彩風(fēng)格更相近。 三、在生成的卡通圖像的基礎(chǔ)上進(jìn)行面部表情的變換。利用圖像變形算法，通過控制主要面部器官特征點(diǎn)的位置，使無表情的卡通人臉變換出微笑、悲傷等形象、生動(dòng)和俏皮的表情。 實(shí)驗(yàn)證明，本文提出的人臉卡通化方法能夠獲得較理想的卡通效果，并且卡通人臉的表情動(dòng)畫生動(dòng)、形象，時(shí)效性高。
[Abstract]:The diversity and uniqueness of human face has always been a hot topic in computer vision, graphics and pattern recognition, and the art of Katonghua leads the development of art with its unique forms and techniques. The combination of the two face cards through the description of lines and color rendering, with its unique exaggeration mode, image and lifelike reproduction of face images, in online games, interactive forums, social software and animation and other fields widely used. The existing learning-based face card generalization methods usually divide the image into several small blocks and realize the cartoon image synthesis by matching and synthesizing the image blocks. However, due to the influence of block effect, The detail description of face features in image is not detailed, and the effect of face line is not good. However, the popular face localization method can get better detail description and line effect through accurate location of face features. This paper mainly studies how a given face image computer can automatically generate a cartoon face image with a specific style of the artist's painting work, and how to make a cartoon facial expression animation transformation. The main research contents are as follows:. Firstly, two learning based cartoon face image generation algorithms are proposed: one is based on parametric model and the other is based on feature point, and the other is based on active apparent model. By learning the process of face matching, we use the method of parameter estimation to generate cartoon face image. Based on feature point, we classify the face features from the perspective of high-level semantics, and synthesize the hair of cartoon face separately. Contour and facial features to achieve cartoon face image generation. Secondly, in order to get a better color cartoon effect, three color rendering methods are used to color the cartoon image. The color space conversion method and the image segmentation method are used respectively. The color color method based on color space conversion is similar to the input image. The coloring method based on image segmentation shows that the color style of cartoon image is more similar to that of artist painting. Third, on the basis of the generated cartoon image, the facial expression is transformed. By controlling the location of the feature points of the main facial organs by using the image deformation algorithm, the expressionless cartoon faces are transformed into images of smile, sadness, etc. A vivid and playful expression. Experimental results show that the proposed method can obtain ideal cartoon effect, and the facial expression of cartoon face is vivid, vivid and time-efficient.
【學(xué)位授予單位】：電子科技大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2013
【分類號(hào)】：TP391.41

【參考文獻(xiàn)】

相關(guān)期刊論文 前10條

1 葛仕明;程義民;曾丹;何兵兵;;基于稀疏特征匹配和形變傳播的無縫圖像拼接[J];電子與信息學(xué)報(bào);2007年12期

2 劉振安;劉tD;;基于SVG的卡通人臉圖形自動(dòng)生成法[J];測(cè)控技術(shù);2006年05期

3 閻曉敏;唐棣;孫巖;;基于圖像的卡通畫掃描線渲染方法[J];計(jì)算機(jī)工程與應(yīng)用;2008年17期

4 謝金融;卜佳俊;;性別分類中頭發(fā)特征提取方法的研究[J];計(jì)算機(jī)工程;2010年07期

5 趙國(guó)英,李華;人體臉部灰度圖像上色的改進(jìn)算法[J];計(jì)算機(jī)輔助設(shè)計(jì)與圖形學(xué)學(xué)報(bào);2004年08期

6 周仁琴;周經(jīng)野;陳益強(qiáng);劉軍發(fā);;基于特征發(fā)現(xiàn)的卡通人臉肖像生成[J];計(jì)算機(jī)輔助設(shè)計(jì)與圖形學(xué)學(xué)報(bào);2006年09期

7 閻芳;費(fèi)廣正;柳婷婷;馬文慧;石民勇;;漫畫風(fēng)格的人臉肖像生成算法[J];計(jì)算機(jī)輔助設(shè)計(jì)與圖形學(xué)學(xué)報(bào);2007年04期

8 欒青;徐迎慶;;人臉像素畫生成算法[J];計(jì)算機(jī)輔助設(shè)計(jì)與圖形學(xué)學(xué)報(bào);2009年12期

9 陳文娟;石民勇;孫慶杰;;利用人臉特征及其關(guān)系的漫畫夸張與合成[J];計(jì)算機(jī)輔助設(shè)計(jì)與圖形學(xué)學(xué)報(bào);2010年01期

10 朱薇;劉利剛;;保色調(diào)的黑白卡通圖像著色方法[J];計(jì)算機(jī)輔助設(shè)計(jì)與圖形學(xué)學(xué)報(bào);2011年03期

相關(guān)碩士學(xué)位論文 前1條

1 張春婷;基于機(jī)器學(xué)習(xí)的人臉卡通化方法研究[D];電子科技大學(xué);2011年

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