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    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/95855


    Title: Face Detection Based on SVM Classification
    Authors: Lin, Hwei-Jen;Wang, Chun-Wei;Pai, I-Chun
    Contributors: 淡江大學資訊工程學系
    Keywords: Face detection;Skin color segmentation;RGB color space;HSV color space;Support vector machine (SVM)
    Date: 2008-11
    Issue Date: 2014-02-13
    Publisher: 臺北縣淡水鎮 : 淡江大學
    Abstract: This paper proposes an improved version of ourpreviously introduced face detection system based onskin color segmentation and neural networks. Thenew system, using a support vector machine (SVM)based method for learning and verification, consistsof several stages. First, the system searches for theregions where faces might exist by using skin colorinformation and forms a so-called skin map. Afterperforming noise removal and some morphologicaloperations on the skin map, it utilizes the aspect ratioof a face to find out possible face blocks, and theneye detection is carried out within each possible faceblock. If an eye pair is detected in a possible faceblock, a region is cropped according to the locationof the two eyes, which is called a face candidate;otherwise it is regarded as a non-face block. Finally,each of the face candidates is verified by a supportvector machine. Experimental results reflects that thenew version improves the verification accuracy of thepreviously proposed system.
    Relation: 第十三屆人工智慧與應用研討會論文集=The 13th conference on artificial intelligence and applications, pp.158-164
    Appears in Collections:[資訊工程學系暨研究所] 會議論文

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