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研究生:林麗玉
研究生(外文):Li-Yu Lin
論文名稱:利用FaceAppearanceModel模擬臉部外觀變化
論文名稱(外文):Modeling Facial Ageing Process with Face Appearance Model
指導教授:李忠謀李忠謀引用關係
學位類別:碩士
校院名稱:國立臺灣師範大學
系所名稱:資訊教育研究所
學門:教育學門
學類:專業科目教育學類
論文種類:學術論文
論文出版年:2002
畢業學年度:90
語文別:中文
論文頁數:81
中文關鍵詞:臉部外觀變化
外文關鍵詞:face appearance modelfuzzy c-means clustering
相關次數:
  • 被引用被引用:2
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  • 下載下載:43
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本研究提出一個模擬因年齡增長所造成之臉部外觀變化的方法。本研究利用 face appearance model 為基礎,以同時解釋臉部外觀的形狀與灰階值變化。為了提高臉部模型的獨特性,利用 fuzzy c-means clustering 將 training set 中的所有人依臉部外觀相似度分群,每群分別建立一組 group face appearance model,以模擬每群特有的臉部外觀變化。接著,透過同一個人於不同年齡的各組參數,建立個別的 ageing function,以描述年齡與臉部外觀變化的關連性。利用 ageing function,求出各個年齡所對應之模型參數後,便可模擬因年齡增長所造成之臉部外觀的變化。實驗中,利用不同分群方式建立 group face appearance models,並比較各種 group face appearance models 模擬臉部外觀變化的結果與原始影像的誤差值。實驗結果顯示,利用臉部外觀相似度將所有人分群,每群分別建立 group face appearance models 的方法,確實能模擬各群中較為獨特的臉部外觀變化,且能提高模擬結果與原始影像的相似度。

This thesis proposes a method for modeling of the facial ageing process. Face appearance model (FAM) is used to model the shape and texture variations of human faces. Fuzzy c-means clustering is applied to group faces in the training set that have similar face appearances. Group face appearance models (group FAM) are built to model the unique variations of face appearance within each group. Ageing function is defined by the model parameters of each individual in different ages. The simulated results are obtained by applying the most typical model parameters of the simulated age to group FAMs. Experimental results showed that using group FAMs can better simulate facial ageing process than the usual face appearance model in terms of both visual perceptions and mathematical similarity measures.

第一章 緒論
1.1 研究動機
1.2 研究範圍與限制
1.3 論文架構
第二章 文獻探討與系統架構
2.1 文獻探討
2.1.1 Ageing的相關研究
2.1.2 臉部模型的類型
2.1.2.1 “Hand Crafted” Models
2.1.2.2 Fourier Series Shape Models
2.1.2.3 Statistical Models of Shape
2.1.2.4 Active Appearance Models(AAM)
2.1.3 年齡變化與臉部老化的關係
2.1.4 本節結語
2.2 模擬臉部外觀變化之系統架構
2.2.1 Face modeling
2.2.2 Ageing simulation
第三章 Face modeling
3.1 Face shape model
3.1.1 Shapes and Landmarks
3.1.2 形狀對齊
3.1.3 模擬 face shapes 的變化情形
3.2 Face texture model
3.2.1 Object Texture
3.2.2 Image Warping
3.2.2.1 Piecewise Affine
3.2.2.2 Pixel Interpolation
3.2.3 模擬face texture的變化情形
3.3 Face appearance model
3.3.1 建立General Face Appearance Model
3.3.2 建立 Group Face Appearance Model
3.4 實驗結果
第四章 Ageing simulation
4.1 分離與年齡相關的參數
4.2 決定新受試者的 ageing function
4.3 模擬新受試者臉部外觀的變化
4.4 實驗結果
4.4.1 模擬training images臉部外觀變化
4.4.2 模擬新影像臉部外觀變化
第五章 實驗與討論
5.1 Group face appearance models 的比較
5.2 模擬臉部外觀變化
5.2.1 模擬training images臉部外觀變化
5.2.2 模擬新影像臉部外觀變化
5.3 實驗討論
第六章 結論
6.1 結論
6.2 未來研究
附錄

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