一种基于Viola-Jones的改进人脸定位算法

An Improved Face Location Algorithm Based on Viola-Jones

Viola-Jones算法能快速定位人脸,但该算法存在对有偏角的人脸出现漏检和对周围环境非人脸区域出现误检的情况。针对该问题,提出一种基于Viola-Jones的改进人脸定位算法。首先将图像中检测到的人脸像素区域排除,再对剩下未被检测出的区域转为YCrCr模式,设定阈值排除大部分环境中非肤色像素的干扰初步筛选出候选人脸区域,再利用形态学方法进一步排除身体其他部位肤色的干扰和环境中近似人脸像素的背景色干扰并对筛选出的区域进行左角度矫正调整和右角度矫正调整,重新检测,准确定位出人脸位置。通过在标准人脸检测库Faces、IMM和AFW上进行实验,结果表明,该算法能有效提高人脸定位的准确性,较原算法在Faces测试库中正确检测率提高5%,在AFW测试库中正确检测率提高9%。

The Viola-Jones algorithm can quickly locate human face,but the algorithm fails to detect faces with deflection angle and fails to detect non-face areas in the surrounding environment.In view of this problem,an improved face positioning algorithm based on Viola-Jones is proposed.Firstly,the area of face pixels detected in the image is excluded,and then the remaining undetected area is converted to YCrCr mode.The threshold is set to exclude interference of non-skin pixels in most environments to preliminarily screen out the candidate face area.Then the morphological method is used to further eliminate the interference of skin color in other parts of the body and the background color interference of similar face pixels in the environment,and the left angle correction adjustment and right angle correction adjustment are carried out for the selected areas,so as to re-detect and accurately locate the face position.The experiment on Faces,IMM and AFW shows that the proposed algorithm can effectively improve the accuracy of the face location,and the correct detection rate in Faces test library and AFW test library is increased by 5%and 9%respectively compared with the original algorithm.