提出一種基于層疊支持向量機的人臉檢測算法，用于復(fù)雜背景灰度圖像的人臉檢測。算法首先用線性支持向量機進行粗篩選，濾去大量非人臉窗口，之后用非線性支持向量機對通過的窗口進行分類。實驗對比數(shù)據(jù)表明,該方法降低了分類器的訓(xùn)練難度，計算復(fù)雜度較低，大大提高了檢測速度。
關(guān)鍵詞：人臉檢測，支持向量機，模式分類

Face Detection Based on Cascade Support Vector Machine QIU Xiaojia ZHAO Xiuying WANG Jikui （Luoyang College Of Technology, Luoyang 471003, Henan） Abstract：An efficient method of face detection based on cascade Support Vector Machine （CSVM）is proposed in this paper. Firstly，a LSVM coarse filter with relatively lower computational complexity is applied to the whole input image to filter out most of the non-face， then follows the NOSVM classifier to make the final decision，so the detection process is speeded
up. The experiment results show that the method can effectively detect faces under complicated background，and the processing time is shorter than using SVM alone.
Keywords：face detection，support vector machine，pattern classification