藉由色彩與形狀特徵值之支持向量模糊分類器的人臉追蹤

此篇論文介紹一種藉由色彩與形狀特徵值之模糊分類器所進行的人臉偵測與追蹤。而此處的分類器則是使用結合了 Takagi-Sugeno 的fuzzy if-then rules , self-splitting k-means 自我分群法與支持向量器 (support vector learning) 所賦予的高等綜合能力的模糊系統：Fuzzy Classifier With Self-Splitting K-menas And Support Vector Learning (FC-SSKSV)。在臉部偵測的整個流程中，首先我們利用 FC-SSKSV 分類器把色彩空間裡的膚色判別出來。而為了去除一些非膚色範圍的雜訊與補強膚色範圍的完整性，我們利用了型態學的“opening”運算及相鄰膚色的補強來進行處理。接下來針對膚色分割出來的人臉候選區找出它的最佳近似橢圓形。然後對人臉候選區進行以 YCbCr 色彩空間為基礎的 Haar 小波轉換，之後可以根據 Haar 小波轉換在人臉候選區裡的表現來定位出眼睛與嘴巴的位置。眼睛、嘴巴與人臉的色彩特徵可以很直接的被提取出來。這些色彩資訊特徵接著與人臉候選區的形態特徵一起被丟入 FC-SSKSV 做最後的人臉判斷。而上述的方法我們利用 pan-tilt-zoom攝影機來實現在即時人臉追蹤系統上。跟其他的分類器及人臉偵測方法比較， FC-SSKSV 及基於其架構所實現人臉偵測的成果是更為進步的。 Contents Abstract (in Chinese)……………………………………………………ii Abstract (in English)…………………………………………………iii Contents………………………………………………………………iv List of Figures…………………………………………………………vi List of Tables……………………………………………………………xi Chapter 1: Introduction……………………………………………1 1.1 Survey and Literature Review…………………………………1 1.2 Organization of the Thesis………………………………………3 Chapter 2: Fuzzy Classifier With Self-Splitting K-means And Support Vector Learning(FC-SSKSV)……5 2.1 FC-SSKSV Rules and Functions……………………………… 5 2.2 Antectdent Part Learning By Self-Splitting K-means Clustering…6 2.3 Consequent Part Parameter Learning By Support Vector Machine ………………………………………………………………………8 2.3.1 Classification by linear SVM………………………………………………8 2.3.2 Parameter Learning by linear SVM………………………………………10 Chapter 3: Skin Color Segmentation………………………………12 3.1 Color Space…………………………………………………………12 3.1.1 Hs Color Space……………………………………………………………13 3.1.2 YCbCr Color Space…………………………………………………………15 3.2 Color Images Segmentation by FC-SSKSV………………………16 3.3 Segmentation with Neighborhood Averaging……………………20 Chapter 4: Human Face Detection……………………………23 4.1 Face Candidates Generation………………………………………23 4.2 Eye-Localization by Haar wavelet and YCbCr color space analysis……………………………………………………………29 4.3 Verification by shape and Color Feature-based…………………39 Chapter 5: Face Tracking……………………………………46 5.1 Kalman Filter……………………………………………………46 5.2 Face Tracking Process……………………………………………48 5.3 Tracking in the scene of multiple persons………………………50 5.4 Tracking with Pan-Tilt-Zoom camera……………………………55 Chapter 6: Experiment………………………………………58 6.1 Skin Color Segmentation Experiment……………………………58 6.2 Face Detection Experiment………………………………………65 6.3 Face Tracking Experiment………………………………………72 Chapter 7: Conclusion……………………………………….75 Reference…………………………………………………………76 [1] E. 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