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系統識別號 U0026-1910201718314000
論文名稱(中文) 紅外熱序列臉部影像分析與應用
論文名稱(英文) The Analysis and Application of Facial Sequence Images with an Infrared Thermal Approach
校院名稱 成功大學
系所名稱(中) 航空太空工程學系
系所名稱(英) Department of Aeronautics & Astronautics
學年度 106
學期 1
出版年 106
研究生(中文) 簡伯霖
研究生(英文) Bo-Lin Jian
學號 P48011048
學位類別 博士
語文別 英文
論文頁數 89頁
口試委員 指導教授-陳介力
召集委員-王大中
口試委員-彭兆仲
口試委員-王國禎
口試委員-劉建宏
口試委員-戴崇禮
口試委員-林志哲
中文關鍵字 影像校準  獨立主成分分析  情緒評估  情緒顯著性地圖  熱影像 
英文關鍵字 Emotion Activation Map  Emotion Assessment  Independent Component Analysis  Image Registration  Thermal Image 
學科別分類
中文摘要 本論文使用國際情緒圖片系統挑選出不同的情緒圖片來誘發受試者的情緒且同步收集人臉紅外熱序列影像,將所收集到的序列影像自動校準並分析臉部溫度反應的狀況。ble首先,提出一套針對人臉紅外線熱序列影像校準流程,考量在不影響受試者舒適度與最小傷害原則的情況下,來降低受試者非意識的頭部晃動所產生之影像偏差。將一張熱影像藉由影像雙眼區域之質心點定位,來決定影像平移以及旋轉處理,產出校準用之固定影像。本研究提出兩階段基因演算法完成熱序列影像的自動校準,再以影像品質評估指標驗證來校準影像的前後差異。藉由上述之流程,進行精確的人臉影像對位;將自動校準後的序列影像進行人臉區域分割,針對每位受測者的前額、鼻子、嘴、左臉頰與右臉頰五個區域計算其平均溫度,以主成分分析方法將特徵值降維,再使用多變量變異數來分析其顯著性,並以支持向量機分類器來驗證中度與重度思覺失調症患者的臉部溫度差異。此結果與腦部額葉造成不對稱情緒理論相符,並且辨識率最高達94.3%。最後提出建構情緒顯著性地圖的演算法,以拆解出獨立的時間序列與對應的空間獨立成分,其中採用變異數分析計算情緒時序模板與時間序列的最大關聯性,此方法可視覺化顯示誘發的情緒與人臉溫度變化的顯著性。
英文摘要 In this paper, different types of emotion images, selected from the international affective picture system were presented to subjects during infrared thermal facial image approach in order to collect sequence images for further analysis and evaluation of changes in facial temperature. First, a set of facial infrared thermal sequence imaging procedures to reduce the image deviation caused by unconscious head shaking without compromising the subject's comfort and resulting in minimal damage is proposed. A thermal image is positioned by the center of mass of the image binocular area to determine the image translation and rotation processing and to output a fixed image for calibration. In this study, the automatic calibration of thermal sequence images was completed by the proposed two-stage gene algorithm, and the difference in images was calibrated by image quality evaluation. Through the above process the precise face images were aligned, the automatic calibration of the sequence image for facial area was segmented, and then the mean temperature of each subject's forehead, nose, mouth, left cheek and right cheek areas were calculated. The features was dimensioned by the principal component analysis method, the significance was analyzed by using the multivariate variance number, and the support vector machine classifier was used to verify the temperature difference of the face of patients with moderate and severe levels of schizophrenia. The results were consistent with the theory as the frontal lobe produced an asymmetrical emotional, with an identification rate of up to 94.3%. Finally, we propose an algorithm to construct the map of emotional significance to disassemble the independent time series and the corresponding independent spatial composition. Analysis of variance was used to calculate the maximum correlation between the emotion sequence template and the time series. This method can visualize the significant evoked emotional and facial temperature changes.
論文目次 摘要 I
ABSTRACT II
ACKNOWLEDGEMENTS IV
CONTENTS V
LIST OF TABLES VIII
LIST OF FIGURES IX
NOMENCLATURES XI
CHAPTER 1. INTRODUCTION 1
1.1 Motivation 1
1.2 Literature Review 2
1.2.1 Infrared Thermal Image Sequence Registration 2
1.2.2 Emotion evoked methods 4
1.2.3 Emotion Recognition 5
1.2.4 Independent Component Analysis of Activation Maps 7
1.3 Structure of the Dissertation 8
CHAPTER 2. MATERIAL RESOURCES, PARTICIPANT DESCRIPTION AND EXPERIMENTAL PROCESS 10
2.1 Participants 10
2.2 Experimental Setup 13
2.3 Stimuli and Paradigm 15
CHAPTER 3. IMAGE SEQUENCE REGISTRATION ANALYSIS AND VERIFICATION 17
3.1 Calibration of the fixed image 17
3.2 Registration of thermal facial sequences 22
3.3 Discussion 29
CHAPTER 4. SCHIZOPHRENIC PATIENTS APPLIED WITH FACIAL IMAGE REGION 35
4.1 Features Extraction and Analysis 38
4.2 MANOVA of Facial Areas in Response to Evoked Emotions 39
4.3 SVM Identification Results using Different Numbers of Features 41
4.4 Discussions 43
CHAPTER 5. FACIAL EMOTIONAL ACTIVATION MAPS WITH IMAGE SEQUENCE 47
5.1 Process of Regional Activation and Construction of the Activation Map 48
5.1.1 Emotion Activation Maps 50
5.1.2 Facial Regions 54
5.2 Discussion 55
CHAPTER 6. CONCLUSIONS 65
REFERENCES 68
APPENDIX 75
PUBLICATION LIST 87
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