Proposed optimization for AdaBoost-based face detection

摘要：

In this paper, a novel approach is proposed for face detection in still image based on the AdaBoost algorithm. First, face candidates are detected by AdaBoost Algorithm. Since a lot of influence might exist, such as size of the image, illumination and noise, some non-faces windows might also be detected as face candidates, or some faces might be missed. In order to solve these problems and get better performances, we take use of skin color information in the YCbCr color space together with the edge information of the color image. In this way, we are able to remove some non-faces that have been wrongly detected as faces and add some possible missed faces as well. Experimental results show that the hit rate could be improved and false alarm could also be reduced by this method.

关键词： AdaBoost skin color segmentation elliptical model canny edge detection

作者: XU Jiu Satoshi Goto

作者单位: Graduate School of Information Production, and System LSI, Waseda University, Japan

会议类型: 国际会议

会议名称: Third International Conference on Digital Image Processing(ICDIP 2011)(第三届数字图像处理国际会议)

会议地点: 成都

会议语种:英文

页码: 36-40

在线出版日期: 2011-04-15（万方平台首次上网日期，不代表论文的发表时间）