A robustness and real-time face detection algorithm in complex background

Liying Lang, Wei-wei Gu
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引用次数: 5

Abstract

Because AdaBoost Cascade face detection algorithm has a very outstanding performance, AdaBoost face detection is the mainstream algorithm currently. But it can produce misjudgment at a similar facial feature regional, particularly in the detection of more complicated image background circumstances misjudgment is even more serious. In view of reasons above, in this paper, a new algorithm was proposed and named A-SCS algorithm, which is increased skin color segmentation after detected face region use the AdaBoost algorithm. This algorithm makes full use of the image useful information, and greatly reduced the possibility of misjudgment. Compare to AdaBoost algorithm and skin color segmentation algorithm, the algorithm mentioned in this paper reduced the false detecting rate in complex background image, At the same time, it is of definite robustness. Simulated experimental results by Matlab indicate that this algorithm is faster and accuracy. Therefore it can be applied to real-time face detection system.
一种复杂背景下鲁棒实时人脸检测算法
由于AdaBoost级联人脸检测算法具有非常突出的性能,因此AdaBoost人脸检测是目前的主流算法。但它会在相似的人脸特征区域产生误判,尤其在检测较为复杂的图像背景情况时,误判更为严重。鉴于以上原因,本文提出了一种新的算法,并命名为a - scs算法,该算法在使用AdaBoost算法检测到人脸区域后增加肤色分割。该算法充分利用了图像的有用信息,大大降低了误判的可能性。与AdaBoost算法和肤色分割算法相比,本文算法降低了复杂背景图像的误检率,同时具有一定的鲁棒性。Matlab仿真实验结果表明,该算法速度快、精度高。因此,它可以应用于实时人脸检测系统。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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