微表情是一種持續時間極為短暫的表情，它能表現出人類試圖壓抑與隱藏的真正情感。本論文以問卷的形式影像訪問受試者，採集臉部變動數據進行分析臉部細微變動的情況、特徵進行量化的研究。藉由臉部嘴巴、眼睛的變動作為指標，建立邏輯斯模型，由參數估計找出每個影響因子對說謊的影響。
本論文對十人進行測謊分析，實證結果發現，嘴巴水平長度越長，越傾向說實話。且嘴巴水平長度與平均長度的差異越大，有較高說謊的機率。眼睛垂直寬度越大，較傾向說實話，且眼睛垂直寬度與平均寬度的差異越大，說謊話的機率越高。當眼睛垂直寬度在極短時間內（一幀）的變動越大，說謊話的可能性越高。
利用五個解釋變數建立了預測模型，本論文的測謊預測模型正確率可達62.17%，實證結果發現受試者在回答涉及隱私及道德性的高風險問題時，能被模型辨識說謊與否的正確率較回答一般資本資料的低風險問題高。若只考慮高風險問題的人臉數據，預測模型能辨識說謊與否的正確率將達到65.38%。

Facial micro-expressions are brief, involuntary expressions appeared on the face of people who are trying to conceal or repress emotions. This paper developed a questionnaire containing control questions and relevant questions. We analyze the motions of key features on the faces and the appearance of the micro-expressions, we quantify the characteristic of telling lies by observing a sequence of frames extracted from videos. In the model, we test several factors which including eyes’ and mouth’s micro movements, and then fit the logistic regression model to find the main effect on the facial movements when telling lies.
The empirical results indicate that people tend to lie while decreasing the horizontal length of their mouths. Furthermore, the vertical width of eyes tends to change significantly in a very short period while lying.
The classification result of model shows that sensitivity = 74.36% as the proportion of deceptive response being classified correctly; and the overall classification accuracy is 62.23%. We also find out that when people are answering high-stakes questions, our model will achieve a 71.79% classification accuracy in deception response with an overall accuracy as 65.38%, which is higher than the accuracy of all data.

第一章 前言 1

第二章 文獻回顧 3

第三章 研究方法與模型設計 7
3.1研究流程與方法 7
3.2邏輯斯迴歸 10
3.3解釋變數 13
第四章 實證結果分析 19
4.1研究結果 19
4.2預測模型建立 22
4.3預測結果分析 23
第五章 結論與後續研究建議 28
5.1結論 28
5.2研究限制及後續研究建議 29

英文參考文獻
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中文參考文獻
[14] 梁靜、顏文靖、吳奇、申尋兵、王甦菁、傅小蘭，2013 ，「微表情研究的進展與展望」，中國科學基金，75-78頁。

[15] 黃曉燁、楊明強、張鵬、李娟，2014.09，「微表情自動識別綜述」，計算機輔助設計與圖形學學報，第26卷第九期，1386-1395頁。

[16] 彭玉偉，2014.03，「理性看待微表情分析技術在偵訊工作中的應用」，山東警察學院學報，第二期總第134期，114-118頁。