臺灣博碩士論文加值系統

傳統教室上課教師點名，人數多時，人工式點名時間長會縮短教師授課時間;另外在網路學習環境中，線上點名更是一大挑戰，所以本論文提出一個自動出席記錄系統之研究，使用人臉影像辨識與支持向量機(Support Vector Machine, SVM)針對學習者人臉辨識，取代教師人工點名，並建置學習者出席記錄資料庫，實驗結果有令人滿意結果可應用在傳統教室與網路學習環境。

In physical classroom, it will reduce teaching time period to obtain student present records. Additionally, it will be a challenge to quickly get student present records in distance learning environment. As a result, the thesis presents an automatic student-present-record system, which applies face recognition to classroom surveillance video to obtain student present records. It also uses support vector machine as a multiclassifier to recognize each students while feeding video into the system. Experimental results demonstrate that the system has satisfying results. It can be applied to physical classroom and distance learning environment to reduce the teacher’s effort of getting student present records.

摘 要...............i
ABSTRACT...............ii
致謝...............iii
目 錄...............iv
表目錄...............vi
圖目錄...............vii
一、 緒論 ...............1
1.1 研究背景...............1
1.2 研究動機...............1
1.3 研究目的...............4
1.4 論文架構...............4
二、 背景方法研討...............5
2.1 彩色影像轉灰階影像...............5
2.2 矩形特徴...............6
2.3 AdaBoost演算法...............8
2.4 影像的縮放...............10
2.5 離散餘弦轉換...............11
2.6 加伯濾波器...............14
2.7 離散小波轉換...............16
2.8 邊緣偵測...............18
2.9 支持向量機...............20
2.9.1 線性支持向量機...............21
2.9.2 非線性支持向量機...............24
2.10 K個臨近法...............26
2.11 效能評估...............27
三、 研究方法...............28
3.1 相關文獻探討...............28
3.1.1 人臉偵測...............30
3.1.2 特徵抽取...............34
3.1.3 人臉辨識...............37
3.2 本論文提出辨識方法...............38
3.3 非人臉過濾模組...............39
3.4 人臉辨識模組...............42
四、 實驗結果...............48
4.1 人臉影像資料庫與實驗環境...............48
4.1.1 ORL人臉資料庫...............48
4.1.2 Yale人臉資料庫...............49
4.1.3 Caltech Faces人臉資料庫...............49
4.1.4 KEM-DL人臉資料庫...............51
4.1.5 KEM-CL人臉資料庫...............51
4.1.6 資料庫差異比較...............52
4.2 人臉偵測NFM實驗結果...............53
4.3 人臉辨識FRM實驗結果...............57
4.3.1 數位學習環境實驗結果...............58
4.3.2 傳統教室環境實驗結果...............59
4.3.3 數位學習與傳統教室環境實驗結果...............60
五、 結論及未來研究...............61
5.1 研究限制...............62
5.2 未來研究...............62
參考文獻...............63

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