一种基于知识的快速人脸检测方法

A Knowledge-Based Approach for Fast Human Face Detection

为了提高人脸检测的速度 ,提出了一种基于知识的快速人脸检测方法 .该方法是采用符合人脸生理结构特征的人脸镶嵌图模型 ,并在分析了足够多的人脸图象样本的基础上 ,针对人脸图象的灰度和边缘信息 ,建立了一种较为完备的知识库 ;为加快检测速度 ,该方法采用多级检测步骤 ,即在粗检测中 ,根据眼睛的特征 ,提出并采用一种新的人脸粗检测算法——广义几何投影方法 ,从而明显地提高了检测速度 .实验结果表明 ,该方法具有较强的鲁棒性 ,能够很好地解决复杂背景下的多人脸检测问题 .由于该方法实现的简单性 ,并容易由硬件实现 ,使得检测速度进一步提高 。

For the speed of detecting human faces in single grayscale scene imgae is slowly, an approach of knowledge based fast face detection is proposed. In the method a tri part mosaic image model is supplied, which is consistent with physical structure features of human face. Basing on this model, knowledge base, including information of edge and gray in images, is established by analyzing fairly enough human face images. Moreover, in order to enhance the speed of detecting face, hierarchical detection processes is adopted. In the process of rough face detection, a new coarse detection method--extended projection which is according with the physical structure features of eyes is presented and applied, which makes it possible to get different scale face candidate region, thus reduces the computation time of face detection greatly. Our experimental results indicate that the approach is high robust, and it is fit to solve the problem of multi face detection in complex background. Because of the algorithm's simpleness, it can be easily achieved by hardware, and this will shorten the time consuming on face detection. This made it possible to detect faces in real time. So it has wide application perspective at fields of visual telephone, intelligent monitor etc.