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研究生:陳聖元
研究生(外文):Sheng-Yuan Chen
論文名稱:設計與實現一個平行人臉偵測器
論文名稱(外文):Design and Implementation of A Parallel Face Detector
指導教授:梁廷宇
指導教授(外文):Tyng-Yeu Liang
學位類別:碩士
校院名稱:國立高雄應用科技大學
系所名稱:電機工程系碩士班
學門:工程學門
學類:電資工程學類
論文種類:學術論文
論文出版年:2007
畢業學年度:95
語文別:中文
中文關鍵詞:人臉偵測器膚色偵測平行擷取人臉眼睛與嘴巴定位
外文關鍵詞:parallel face detectorskin colormouth positioneye positionJava threads
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人臉偵測器的關鍵在於其偵測器的準確性以及即時性。然而先前的人臉偵測系統裡,不是沒辦法同時偵測多張人臉,就是無法快速且有效的擷取影像中多張人臉。除此之外,一般人臉偵測系統的影像大小都不算太大,基本上都是以320 x 240為主。這是由於當影像太大時,計算時間過長導致系統效能不彰。因此本論文針對動態影像(如:網路攝影機)實現一個可同時快速的擷取多張人臉的平行偵測器。為了提高偵測器的速度,本論文採用膚色偵測做初步判定,再藉由眼睛與嘴巴特徵定位來做為人臉的偵測特徵,最後導入平行處理的機制,即利用Java Multi Thread中的Fork與Join方式使人臉偵測的過程平行化,藉以提昇人臉偵測系統的效能。
Precisely catching faces in real time is a key point of face detectors. However, the proposed face detectors neither catch multiple faces at the same time nor quickly and correctly catch all of the faces in each frame. In addition, most of face detectors work well only when the resolution of images is 320 x 240. The main reason is that the computation cost of face detection increases too big to be tolerant if the image resolution becomes high. To resolve these problems, this paper is aimed at the development of a parallel face detector which can effectively reduces the time of face detection, and simultaneously catches all the faces of persons appearing in each video frame. In order to enhance the speed of face detection, the proposed face detector uses the skin color to margin face candidates in frames, and then apply the position of eyes and mouths to decide whether each face candidate is indeed a face or not. Moreover, the proposed face detector is implemented by Java threads. As a result, it can effectively exploit the computational power of multiprocessors or multi-core processors to speed up the process of face detection, and can be executed on any platform.
摘 要 I
ABSTRACT II
目 錄 III
圖 目 錄 V
表 目 錄 VII
第一章 緒論 1
1.1研究背景 1
1.2 研究動機與目的 2
1.3論文架構 3
第二章 文獻探討 4
2.1 人臉偵測基礎 4
2.2 人臉偵測方法 5
第三章 人臉偵測演算法 8
3.1 演算法流程 8
3.2 光線補償 9
3.3 色彩空間 12
3.3.1 RGB 色彩空間 12
3.3.2 YUV 色彩空間 14
3.3.3 YCbCr色彩空間 14
3.4 膚色偵測 15
3.5去除雜訊 21
3.6嘴巴定位 23
3.7 眼睛定位 25
3.8 演算法之平行 29
第四章 實驗結果與討論 31
4.1 實作環境 31
4.2膚色偵測實測結果 31
4.2.1 不同光源之膚色偵測 31
4.2.2 人臉可能區域及定位 33
4.3 嘴巴偵測實測結果 34
4.4 眼睛偵測實測結果 35
4.5 人臉偵測之平行時間實測結果 37
第五章 結論與未來工作 42
參考文獻 44
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