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研究生:鍾季叡
研究生(外文):CHUNG, CHI-JUI
論文名稱:應用於大型頭部姿勢旋轉的眼睛中心定位新方法
論文名稱(外文):A Novel Eye Center Localization in Head Poses with Large Rotations
指導教授:許巍嚴
指導教授(外文):HSU, WEI-YEN
口試委員:林維暘劉偉名
口試委員(外文):LIN, WEI-YANGLIU, WEI-MIN
口試日期:2020-06-24
學位類別:碩士
校院名稱:國立中正大學
系所名稱:資訊管理系研究所
學門:電算機學門
學類:電算機一般學類
論文種類:學術論文
論文出版年:2020
畢業學年度:108
語文別:中文
論文頁數:61
中文關鍵詞:眼睛中心定位大型頭部旋轉影像轉換學習幾何轉換
外文關鍵詞:Eye center localizationLarge head rotationsImage translation learningGeometric transformation
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第一章 緒論 1
1.1 研究背景 1
1.2 研究動機 4
1.3 研究問題與目的 6
1.4 研究成果與貢獻 7
第二章 文獻探討 8
2.1 眼睛中心定位之相關文獻 8
2.1.1 基於形狀方法 (Shape-Based Methods) 9
2.1.2 基於特徵的形狀方法 (Feature-Based Shape Methods) 12
2.1.3 基於外觀方法 (Appearance-Based Methods) 15
2.1.4 基於混合方法 (Hybrid-Based Methods) 17
2.1.5 頭部旋轉變化的眼睛定位 (Eye detection under head rotations) 18
2.2 生成對抗網路之相關文獻 20
2.2.1 完全連接GAN (Fully connected GAN) 20
2.2.2 卷積GAN (Convolutional GAN) 20
2.2.3 條件GAN (Conditional GAN) 21
2.2.4 推理模型GAN (GAN with inference models) 22
2.2.5 對抗自編碼器 (Adversarial autoencoders) 22
2.2.6 正面臉部生成的GAN (Frontal Face Generation under GAN) 24
第三章 材料與研究方法 25
3.1 實驗材料 25
3.1.1 Extended Yale Face Database B 25
3.1.2 CMU Multi-PIE Database 26
3.1.3 Color FERET Database 26
3.1.4 Gi4E Database 27
3.1.5 BioID Database 27
3.2 研究架構與流程 28
3.3 研究方法之步驟 29
3.3.1 CR-pipeline (前端):用於Large Head Rotations的臉部檢測器 29
3.3.2 CR-pipeline (中端):正面臉部生成 30
3.3.3 CR-Pipeline (末端):兩種CRs的萃取 31
3.3.4 眼睛中心定位:基於幾何轉換的DCC方法 33
3.3.5 眼睛中心定位:基於影像轉換學習的ITC方法 35
第四章 實驗結果與討論 37
4.1 實驗環境 37
4.2 實驗評估指標 37
4.3 實驗結果1:照明和頭部姿勢的穩定性 38
4.4 實驗結果2:凝視互動的穩定性 41
4.5 實驗結果3:Large Yaw-Rotation in Large Head Rotations的穩定性 42
4.6 實驗結果4:Large Head Rotations的穩定性 43
4.7 實驗結果5:雙眼完全遮蔽的穩定性 44
第五章 結論與未來展望 46
5.1. 結論 46
5.2. 未來展望 46
參考文獻 48
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